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breathe-horizontal" role="navigation" aria-label="pagination"> <a href="" class="pagination-previous is-invisible">Previous </a> <a href="/search/?searchtype=author&query=Chen%2C+L&start=50" class="pagination-next" >Next </a> <ul class="pagination-list"> <li> <a href="/search/?searchtype=author&query=Chen%2C+L&start=0" class="pagination-link is-current" aria-label="Goto page 1">1 </a> </li> <li> <a href="/search/?searchtype=author&query=Chen%2C+L&start=50" class="pagination-link " aria-label="Page 2" aria-current="page">2 </a> </li> <li> <a href="/search/?searchtype=author&query=Chen%2C+L&start=100" class="pagination-link " aria-label="Page 3" aria-current="page">3 </a> </li> <li> <a href="/search/?searchtype=author&query=Chen%2C+L&start=150" class="pagination-link " aria-label="Page 4" aria-current="page">4 </a> </li> <li> <a href="/search/?searchtype=author&query=Chen%2C+L&start=200" class="pagination-link " aria-label="Page 5" aria-current="page">5 </a> </li> <li><span class="pagination-ellipsis">…</span></li> </ul> </nav> <ol class="breathe-horizontal" start="1"> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.14279">arXiv:2411.14279</a> <span> [<a href="https://arxiv.org/pdf/2411.14279">pdf</a>, <a href="https://arxiv.org/format/2411.14279">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> </div> </div> <p class="title is-5 mathjax"> Looking Beyond Text: Reducing Language bias in Large Vision-Language Models via Multimodal Dual-Attention and Soft-Image Guidance </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Zhao%2C+H">Haozhe Zhao</a>, <a href="/search/?searchtype=author&query=Si%2C+S">Shuzheng Si</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Liang Chen</a>, <a href="/search/?searchtype=author&query=Zhang%2C+Y">Yichi Zhang</a>, <a href="/search/?searchtype=author&query=Sun%2C+M">Maosong Sun</a>, <a href="/search/?searchtype=author&query=Zhang%2C+M">Mingjia Zhang</a>, <a href="/search/?searchtype=author&query=Chang%2C+B">Baobao Chang</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.14279v1-abstract-short" style="display: inline;"> Large vision-language models (LVLMs) have achieved impressive results in various vision-language tasks. However, despite showing promising performance, LVLMs suffer from hallucinations caused by language bias, leading to diminished focus on images and ineffective visual comprehension. We identify two primary reasons for this bias: 1. Different scales of training data between the pretraining stage… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.14279v1-abstract-full').style.display = 'inline'; document.getElementById('2411.14279v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.14279v1-abstract-full" style="display: none;"> Large vision-language models (LVLMs) have achieved impressive results in various vision-language tasks. However, despite showing promising performance, LVLMs suffer from hallucinations caused by language bias, leading to diminished focus on images and ineffective visual comprehension. We identify two primary reasons for this bias: 1. Different scales of training data between the pretraining stage of LLM and multimodal alignment stage. 2. The learned inference bias due to short-term dependency of text data. Therefore, we propose LACING, a systemic framework designed to address the language bias of LVLMs with muLtimodal duAl-attention meChanIsm (MDA) aNd soft-image Guidance (IFG). Specifically, MDA introduces a parallel dual-attention mechanism that enhances the integration of visual inputs across the model. IFG introduces a learnable soft visual prompt during training and inference to replace visual inputs, designed to compel LVLMs to prioritize text inputs. Then, IFG further proposes a novel decoding strategy using the soft visual prompt to mitigate the model's over-reliance on adjacent text inputs. Comprehensive experiments demonstrate that our method effectively debiases LVLMs from their language bias, enhancing visual comprehension and reducing hallucinations without requiring additional training resources or data. The code and model are available at [lacing-lvlm.github.io](https://lacing-lvlm.github.io). <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.14279v1-abstract-full').style.display = 'none'; document.getElementById('2411.14279v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 21 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">19 pages, 12 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.14053">arXiv:2411.14053</a> <span> [<a href="https://arxiv.org/pdf/2411.14053">pdf</a>, <a href="https://arxiv.org/format/2411.14053">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> </div> </div> <p class="title is-5 mathjax"> Stereo Anything: Unifying Stereo Matching with Large-Scale Mixed Data </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Guo%2C+X">Xianda Guo</a>, <a href="/search/?searchtype=author&query=Zhang%2C+C">Chenming Zhang</a>, <a href="/search/?searchtype=author&query=Zhang%2C+Y">Youmin Zhang</a>, <a href="/search/?searchtype=author&query=Nie%2C+D">Dujun Nie</a>, <a href="/search/?searchtype=author&query=Wang%2C+R">Ruilin Wang</a>, <a href="/search/?searchtype=author&query=Zheng%2C+W">Wenzhao Zheng</a>, <a href="/search/?searchtype=author&query=Poggi%2C+M">Matteo Poggi</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Long Chen</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.14053v1-abstract-short" style="display: inline;"> Stereo matching has been a pivotal component in 3D vision, aiming to find corresponding points between pairs of stereo images to recover depth information. In this work, we introduce StereoAnything, a highly practical solution for robust stereo matching. Rather than focusing on a specialized model, our goal is to develop a versatile foundational model capable of handling stereo images across diver… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.14053v1-abstract-full').style.display = 'inline'; document.getElementById('2411.14053v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.14053v1-abstract-full" style="display: none;"> Stereo matching has been a pivotal component in 3D vision, aiming to find corresponding points between pairs of stereo images to recover depth information. In this work, we introduce StereoAnything, a highly practical solution for robust stereo matching. Rather than focusing on a specialized model, our goal is to develop a versatile foundational model capable of handling stereo images across diverse environments. To this end, we scale up the dataset by collecting labeled stereo images and generating synthetic stereo pairs from unlabeled monocular images. To further enrich the model's ability to generalize across different conditions, we introduce a novel synthetic dataset that complements existing data by adding variability in baselines, camera angles, and scene types. We extensively evaluate the zero-shot capabilities of our model on five public datasets, showcasing its impressive ability to generalize to new, unseen data. Code will be available at \url{https://github.com/XiandaGuo/OpenStereo}. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.14053v1-abstract-full').style.display = 'none'; document.getElementById('2411.14053v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 21 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Code will be available at \url{https://github.com/XiandaGuo/OpenStereo}</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.13898">arXiv:2411.13898</a> <span> [<a href="https://arxiv.org/pdf/2411.13898">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Strongly Correlated Electrons">cond-mat.str-el</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Mesoscale and Nanoscale Physics">cond-mat.mes-hall</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Materials Science">cond-mat.mtrl-sci</span> </div> </div> <p class="title is-5 mathjax"> Discovery of an Antiferromagnetic Topological Nodal-line Kondo Semimetal </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Liu%2C+D+F">D. F. Liu</a>, <a href="/search/?searchtype=author&query=Xu%2C+Y+F">Y. F. Xu</a>, <a href="/search/?searchtype=author&query=Hu%2C+H+Y">H. Y. Hu</a>, <a href="/search/?searchtype=author&query=Liu%2C+J+Y">J. Y. Liu</a>, <a href="/search/?searchtype=author&query=Ying%2C+T+P">T. P. Ying</a>, <a href="/search/?searchtype=author&query=Lv%2C+Y+Y">Y. Y. Lv</a>, <a href="/search/?searchtype=author&query=Jiang%2C+Y">Y. Jiang</a>, <a href="/search/?searchtype=author&query=Chen%2C+C">C. Chen</a>, <a href="/search/?searchtype=author&query=Yang%2C+Y+H">Y. H. Yang</a>, <a href="/search/?searchtype=author&query=Pei%2C+D">D. Pei</a>, <a href="/search/?searchtype=author&query=Prabhakaran%2C+D">D. Prabhakaran</a>, <a href="/search/?searchtype=author&query=Gao%2C+M+H">M. H. Gao</a>, <a href="/search/?searchtype=author&query=Wang%2C+J+J">J. J. Wang</a>, <a href="/search/?searchtype=author&query=Zhang%2C+Q+H">Q. H. Zhang</a>, <a href="/search/?searchtype=author&query=Meng%2C+F+Q">F. Q. Meng</a>, <a href="/search/?searchtype=author&query=Thiagarajan%2C+B">B. Thiagarajan</a>, <a href="/search/?searchtype=author&query=Polley%2C+C">C. Polley</a>, <a href="/search/?searchtype=author&query=Hashimoto%2C+M">M. Hashimoto</a>, <a href="/search/?searchtype=author&query=Lu%2C+D+H">D. H. Lu</a>, <a href="/search/?searchtype=author&query=Schr%C3%B6ter%2C+N+B+M">N. B. M. Schr枚ter</a>, <a href="/search/?searchtype=author&query=Strocov%2C+V+N">V. N. Strocov</a>, <a href="/search/?searchtype=author&query=Louat%2C+A">A. Louat</a>, <a href="/search/?searchtype=author&query=Cacho%2C+C">C. Cacho</a>, <a href="/search/?searchtype=author&query=Biswas%2C+D">D. Biswas</a>, <a href="/search/?searchtype=author&query=Lee%2C+T+-">T. -L. Lee</a> , et al. (12 additional authors not shown) </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.13898v1-abstract-short" style="display: inline;"> The symbiosis of strong interactions, flat bands, topology and symmetry has led to the discovery of exotic phases of matter, including fractional Chern insulators, correlated moir茅 topological superconductors, and Dirac and Weyl semimetals. Correlated metals, such as those present in Kondo lattices, rely on the screening of local moments by a sea of non-magnetic conduction electrons. Here, we repo… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.13898v1-abstract-full').style.display = 'inline'; document.getElementById('2411.13898v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.13898v1-abstract-full" style="display: none;"> The symbiosis of strong interactions, flat bands, topology and symmetry has led to the discovery of exotic phases of matter, including fractional Chern insulators, correlated moir茅 topological superconductors, and Dirac and Weyl semimetals. Correlated metals, such as those present in Kondo lattices, rely on the screening of local moments by a sea of non-magnetic conduction electrons. Here, we report on a unique topological Kondo lattice compound, CeCo2P2, where the Kondo effect - whose existence under the magnetic Co phase is protected by PT symmetry - coexists with antiferromagnetic order emerging from the flat bands associated with the Co atoms. Remarkably, this is the only known Kondo lattice compound where magnetic order occurs in non-heavy electrons, and puzzlingly, at a temperature significantly higher than that of the Kondo effect. Furthermore, at low temperatures, the emergence of the Kondo effect, in conjunction with a glide-mirror-z symmetry, results in a nodal line protected by bulk topology near the Fermi energy. These unusual properties, arising from the interplay between itinerant and correlated electrons from different constituent elements, lead to novel quantum phases beyond the celebrated topological Kondo insulators and Weyl Kondo semimetals. CeCo2P2 thus provides an ideal platform for investigating narrow bands, topology, magnetism, and the Kondo effect in strongly correlated electron systems. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.13898v1-abstract-full').style.display = 'none'; document.getElementById('2411.13898v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 21 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">17pages,4 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.13765">arXiv:2411.13765</a> <span> [<a href="https://arxiv.org/pdf/2411.13765">pdf</a>, <a href="https://arxiv.org/ps/2411.13765">ps</a>, <a href="https://arxiv.org/format/2411.13765">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Probability">math.PR</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Optimization and Control">math.OC</span> </div> </div> <p class="title is-5 mathjax"> Schr枚dinger Bridge Problem for Jump Diffusions </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Zlotchevski%2C+A">Andrei Zlotchevski</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Linan Chen</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.13765v1-abstract-short" style="display: inline;"> The Schr枚dinger bridge problem (SBP) seeks to find the measure $\hat{\mathbf{P}}$ on a certain path space which interpolates between state-space distributions $蟻_0$ at time $0$ and $蟻_T$ at time $T$ while minimizing the KL divergence (relative entropy) to a reference path measure $\mathbf{R}$. In this work, we tackle the SBP in the case when $\mathbf{R}$ is the path measure of a jump diffusion. Un… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.13765v1-abstract-full').style.display = 'inline'; document.getElementById('2411.13765v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.13765v1-abstract-full" style="display: none;"> The Schr枚dinger bridge problem (SBP) seeks to find the measure $\hat{\mathbf{P}}$ on a certain path space which interpolates between state-space distributions $蟻_0$ at time $0$ and $蟻_T$ at time $T$ while minimizing the KL divergence (relative entropy) to a reference path measure $\mathbf{R}$. In this work, we tackle the SBP in the case when $\mathbf{R}$ is the path measure of a jump diffusion. Under mild assumptions, with both the operator theory approach and the stochastic calculus techniques, we establish an $h$-transform theory for jump diffusions and devise an approximation method to achieve the jump-diffusion SBP solution $\hat{\mathbf{P}}$ as the strong-convergence limit of a sequence of harmonic $h$-transforms. To the best of our knowledge, these results are novel in the study of SBP. Moreover, the $h$-transform framework and the approximation method developed in this work are robust and applicable to a relatively general class of jump diffusions. In addition, we examine the SBP of particular types of jump diffusions under additional regularity conditions and extend the existing results on the SBP from the diffusion case to the jump-diffusion setting. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.13765v1-abstract-full').style.display = 'none'; document.getElementById('2411.13765v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 20 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">MSC Class:</span> 35Q93; 45K05; 60H10; 60H20; 60H30; 94A17 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.13599">arXiv:2411.13599</a> <span> [<a href="https://arxiv.org/pdf/2411.13599">pdf</a>, <a href="https://arxiv.org/format/2411.13599">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Statistical Finance">q-fin.ST</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> </div> </div> <p class="title is-5 mathjax"> Can ChatGPT Overcome Behavioral Biases in the Financial Sector? Classify-and-Rethink: Multi-Step Zero-Shot Reasoning in the Gold Investment </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Liu%2C+S">Shuoling Liu</a>, <a href="/search/?searchtype=author&query=Jia%2C+G">Gaoguo Jia</a>, <a href="/search/?searchtype=author&query=Jiang%2C+Y">Yuhang Jiang</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Liyuan Chen</a>, <a href="/search/?searchtype=author&query=Yang%2C+Q">Qiang Yang</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.13599v1-abstract-short" style="display: inline;"> Large Language Models (LLMs) have achieved remarkable success recently, displaying exceptional capabilities in creating understandable and organized text. These LLMs have been utilized in diverse fields, such as clinical research, where domain-specific models like Med-Palm have achieved human-level performance. Recently, researchers have employed advanced prompt engineering to enhance the general… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.13599v1-abstract-full').style.display = 'inline'; document.getElementById('2411.13599v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.13599v1-abstract-full" style="display: none;"> Large Language Models (LLMs) have achieved remarkable success recently, displaying exceptional capabilities in creating understandable and organized text. These LLMs have been utilized in diverse fields, such as clinical research, where domain-specific models like Med-Palm have achieved human-level performance. Recently, researchers have employed advanced prompt engineering to enhance the general reasoning ability of LLMs. Despite the remarkable success of zero-shot Chain-of-Thoughts (CoT) in solving general reasoning tasks, the potential of these methods still remains paid limited attention in the financial reasoning task.To address this issue, we explore multiple prompt strategies and incorporated semantic news information to improve LLMs' performance on financial reasoning tasks.To the best of our knowledge, we are the first to explore this important issue by applying ChatGPT to the gold investment.In this work, our aim is to investigate the financial reasoning capabilities of LLMs and their capacity to generate logical and persuasive investment opinions. We will use ChatGPT, one of the most powerful LLMs recently, and prompt engineering to achieve this goal. Our research will focus on understanding the ability of LLMs in sophisticated analysis and reasoning within the context of investment decision-making. Our study finds that ChatGPT with CoT prompt can provide more explainable predictions and overcome behavioral biases, which is crucial in finance-related tasks and can achieve higher investment returns. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.13599v1-abstract-full').style.display = 'none'; document.getElementById('2411.13599v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 19 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.13285">arXiv:2411.13285</a> <span> [<a href="https://arxiv.org/pdf/2411.13285">pdf</a>, <a href="https://arxiv.org/ps/2411.13285">ps</a>, <a href="https://arxiv.org/format/2411.13285">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Functional Analysis">math.FA</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1016/S0550-3213(01)00405-9">10.1016/S0550-3213(01)00405-9 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> On the $L_{\mathrm{YJ}}(尉, 畏, X)$ constant for the Bana艣-Fr膮czek space </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Wang%2C+Y">Yuxin Wang</a>, <a href="/search/?searchtype=author&query=Liu%2C+Q">Qi Liu</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Linhui Chen</a>, <a href="/search/?searchtype=author&query=Tan%2C+X">Xiewei Tan</a>, <a href="/search/?searchtype=author&query=Sarfraz%2C+M">Muhammad Sarfraz</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.13285v1-abstract-short" style="display: inline;"> In this paper, for any $位\geq 1, R_位^2$ is the Bana艣-Fr膮czek space. The exact value of $L_{\mathrm{YJ}}(尉, 畏, X)$ for this space will be calculated. Specifically, $L_{\mathrm{YJ}}\left(尉, 畏, R_位^2\right)=1+\frac{2 尉畏}{尉^2+畏^2}\left(1-\frac{1}{位^2}\right)$ is the result thereafter through meticilous computation. </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.13285v1-abstract-full" style="display: none;"> In this paper, for any $位\geq 1, R_位^2$ is the Bana艣-Fr膮czek space. The exact value of $L_{\mathrm{YJ}}(尉, 畏, X)$ for this space will be calculated. Specifically, $L_{\mathrm{YJ}}\left(尉, 畏, R_位^2\right)=1+\frac{2 尉畏}{尉^2+畏^2}\left(1-\frac{1}{位^2}\right)$ is the result thereafter through meticilous computation. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.13285v1-abstract-full').style.display = 'none'; document.getElementById('2411.13285v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 20 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">for associated mpeg file, see http://myhost.domain/file.mpg</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Report number:</span> Report-no: EFI-94-11 <span class="has-text-black-bis has-text-weight-semibold">MSC Class:</span> 46B20 <span class="has-text-black-bis has-text-weight-semibold">ACM Class:</span> F.2.2; I.2.7 </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> J.Hasty Results 1 (2008) 1-9; Erratum: J.Hasty Results 2 (2008) 1-2 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.13112">arXiv:2411.13112</a> <span> [<a href="https://arxiv.org/pdf/2411.13112">pdf</a>, <a href="https://arxiv.org/format/2411.13112">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> </div> </div> <p class="title is-5 mathjax"> DriveMLLM: A Benchmark for Spatial Understanding with Multimodal Large Language Models in Autonomous Driving </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Guo%2C+X">Xianda Guo</a>, <a href="/search/?searchtype=author&query=Zhang%2C+R">Ruijun Zhang</a>, <a href="/search/?searchtype=author&query=Duan%2C+Y">Yiqun Duan</a>, <a href="/search/?searchtype=author&query=He%2C+Y">Yuhang He</a>, <a href="/search/?searchtype=author&query=Zhang%2C+C">Chenming Zhang</a>, <a href="/search/?searchtype=author&query=Liu%2C+S">Shuai Liu</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Long Chen</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.13112v1-abstract-short" style="display: inline;"> Autonomous driving requires a comprehensive understanding of 3D environments to facilitate high-level tasks such as motion prediction, planning, and mapping. In this paper, we introduce DriveMLLM, a benchmark specifically designed to evaluate the spatial understanding capabilities of multimodal large language models (MLLMs) in autonomous driving. DriveMLLM includes 2,734 front-facing camera images… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.13112v1-abstract-full').style.display = 'inline'; document.getElementById('2411.13112v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.13112v1-abstract-full" style="display: none;"> Autonomous driving requires a comprehensive understanding of 3D environments to facilitate high-level tasks such as motion prediction, planning, and mapping. In this paper, we introduce DriveMLLM, a benchmark specifically designed to evaluate the spatial understanding capabilities of multimodal large language models (MLLMs) in autonomous driving. DriveMLLM includes 2,734 front-facing camera images and introduces both absolute and relative spatial reasoning tasks, accompanied by linguistically diverse natural language questions. To measure MLLMs' performance, we propose novel evaluation metrics focusing on spatial understanding. We evaluate several state-of-the-art MLLMs on DriveMLLM, and our results reveal the limitations of current models in understanding complex spatial relationships in driving contexts. We believe these findings underscore the need for more advanced MLLM-based spatial reasoning methods and highlight the potential for DriveMLLM to drive further research in autonomous driving. Code will be available at \url{https://github.com/XiandaGuo/Drive-MLLM}. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.13112v1-abstract-full').style.display = 'none'; document.getElementById('2411.13112v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 20 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Code will be available at \url{https://github.com/XiandaGuo/Drive-MLLM}</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.13070">arXiv:2411.13070</a> <span> [<a href="https://arxiv.org/pdf/2411.13070">pdf</a>, <a href="https://arxiv.org/ps/2411.13070">ps</a>, <a href="https://arxiv.org/format/2411.13070">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Strongly Correlated Electrons">cond-mat.str-el</span> </div> </div> <p class="title is-5 mathjax"> Persistent Spin Dynamics in the Ising Triangular-lattice Antiferromagnet Ba$_6$Nd$_2$Ti$_4$O$_{17}$ </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Jiang%2C+C+Y">C. Y. Jiang</a>, <a href="/search/?searchtype=author&query=Chen%2C+B+L">B. L. Chen</a>, <a href="/search/?searchtype=author&query=Chen%2C+K+W">K. W. Chen</a>, <a href="/search/?searchtype=author&query=Jiao%2C+J+C">J. C. Jiao</a>, <a href="/search/?searchtype=author&query=Wang%2C+Y">Y. Wang</a>, <a href="/search/?searchtype=author&query=Wu%2C+Q">Q. Wu</a>, <a href="/search/?searchtype=author&query=Zhang%2C+N+Y">N. Y. Zhang</a>, <a href="/search/?searchtype=author&query=Zou%2C+M+Y">M. Y. Zou</a>, <a href="/search/?searchtype=author&query=Ho%2C+P+-">P. -C. Ho</a>, <a href="/search/?searchtype=author&query=Bernal%2C+O+O">O. O. Bernal</a>, <a href="/search/?searchtype=author&query=Shu%2C+L">L. Shu</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.13070v1-abstract-short" style="display: inline;"> We report results of magnetic susceptibility, specific heat, and muon spin relaxation ($渭$SR) measurements on the polycrystalline Ba$_6$Nd$_2$Ti$_4$O$_{17}$, a disorder-free triangular-lattice antiferromagnet. The absence of long-range magnetic order or spin freezing is confirmed down to 30~mK, much less than the Curie-Weiss temperature -1.8~K. The magnetic and specific heat measurements reveal th… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.13070v1-abstract-full').style.display = 'inline'; document.getElementById('2411.13070v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.13070v1-abstract-full" style="display: none;"> We report results of magnetic susceptibility, specific heat, and muon spin relaxation ($渭$SR) measurements on the polycrystalline Ba$_6$Nd$_2$Ti$_4$O$_{17}$, a disorder-free triangular-lattice antiferromagnet. The absence of long-range magnetic order or spin freezing is confirmed down to 30~mK, much less than the Curie-Weiss temperature -1.8~K. The magnetic and specific heat measurements reveal the effective-1/2 spins are Ising-like. The persistent spin dynamics is determined down to 37~mK. Our study present a remarkable example of Ising spins on the triangular lattice, which remains magnetically disordered at low temperatures and potentially hosts a quantum spin liquid ground state. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.13070v1-abstract-full').style.display = 'none'; document.getElementById('2411.13070v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 20 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.12853">arXiv:2411.12853</a> <span> [<a href="https://arxiv.org/pdf/2411.12853">pdf</a>, <a href="https://arxiv.org/format/2411.12853">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Biomolecules">q-bio.BM</span> </div> </div> <p class="title is-5 mathjax"> Integrating Secondary Structures Information into Triangular Spatial Relationships (TSR) for Advanced Protein Classification </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Khajouie%2C+P">Poorya Khajouie</a>, <a href="/search/?searchtype=author&query=Sarkar%2C+T">Titli Sarkar</a>, <a href="/search/?searchtype=author&query=Rauniyar%2C+K">Krishna Rauniyar</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Li Chen</a>, <a href="/search/?searchtype=author&query=Xu%2C+W">Wu Xu</a>, <a href="/search/?searchtype=author&query=Raghavan%2C+V">Vijay Raghavan</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.12853v1-abstract-short" style="display: inline;"> Protein structures represent the key to deciphering biological functions. The more detailed form of similarity among these proteins is sometimes overlooked by the conventional structural comparison methods. In contrast, further advanced methods, such as Triangular Spatial Relationship (TSR), have been demonstrated to make finer differentiations. Still, the classical implementation of TSR does not… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.12853v1-abstract-full').style.display = 'inline'; document.getElementById('2411.12853v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.12853v1-abstract-full" style="display: none;"> Protein structures represent the key to deciphering biological functions. The more detailed form of similarity among these proteins is sometimes overlooked by the conventional structural comparison methods. In contrast, further advanced methods, such as Triangular Spatial Relationship (TSR), have been demonstrated to make finer differentiations. Still, the classical implementation of TSR does not provide for the integration of secondary structure information, which is important for a more detailed understanding of the folding pattern of a protein. To overcome these limitations, we developed the SSE-TSR approach. The proposed method integrates secondary structure elements (SSEs) into TSR-based protein representations. This allows an enriched representation of protein structures by considering 18 different combinations of helix, strand, and coil arrangements. Our results show that using SSEs improves the accuracy and reliability of protein classification to varying degrees. We worked with two large protein datasets of 9.2K and 7.8K samples, respectively. We applied the SSE-TSR approach and used a neural network model for classification. Interestingly, introducing SSEs improved performance statistics for Dataset 1, with accuracy moving from 96.0% to 98.3%. For Dataset 2, where the performance statistics were already good, further small improvements were found with the introduction of SSE, giving an accuracy of 99.5% compared to 99.4%. These results show that SSE integration can dramatically improve TSR key discrimination, with significant benefits in datasets with low initial accuracies and only incremental gains in those with high baseline performance. Thus, SSE-TSR is a powerful bioinformatics tool that improves protein classification and understanding of protein function and interaction. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.12853v1-abstract-full').style.display = 'none'; document.getElementById('2411.12853v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 19 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.12840">arXiv:2411.12840</a> <span> [<a href="https://arxiv.org/pdf/2411.12840">pdf</a>, <a href="https://arxiv.org/format/2411.12840">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Statistics Theory">math.ST</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Logic in Computer Science">cs.LO</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Category Theory">math.CT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Probability">math.PR</span> </div> </div> <p class="title is-5 mathjax"> The Aldous--Hoover Theorem in Categorical Probability </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Chen%2C+L">Leihao Chen</a>, <a href="/search/?searchtype=author&query=Fritz%2C+T">Tobias Fritz</a>, <a href="/search/?searchtype=author&query=Gonda%2C+T">Tom谩拧 Gonda</a>, <a href="/search/?searchtype=author&query=Klingler%2C+A">Andreas Klingler</a>, <a href="/search/?searchtype=author&query=Lorenzin%2C+A">Antonio Lorenzin</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.12840v1-abstract-short" style="display: inline;"> The Aldous-Hoover Theorem concerns an infinite matrix of random variables whose distribution is invariant under finite permutations of rows and columns. It states that, up to equality in distribution, each random variable in the matrix can be expressed as a function only depending on four key variables: one common to the entire matrix, one that encodes information about its row, one that encodes i… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.12840v1-abstract-full').style.display = 'inline'; document.getElementById('2411.12840v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.12840v1-abstract-full" style="display: none;"> The Aldous-Hoover Theorem concerns an infinite matrix of random variables whose distribution is invariant under finite permutations of rows and columns. It states that, up to equality in distribution, each random variable in the matrix can be expressed as a function only depending on four key variables: one common to the entire matrix, one that encodes information about its row, one that encodes information about its column, and a fourth one specific to the matrix entry. We state and prove the theorem within a category-theoretic approach to probability, namely the theory of Markov categories. This makes the proof more transparent and intuitive when compared to measure-theoretic ones. A key role is played by a newly identified categorical property, the Cauchy--Schwarz axiom, which also facilitates a new synthetic de Finetti Theorem. We further provide a variant of our proof using the ordered Markov property and the d-separation criterion, both generalized from Bayesian networks to Markov categories. We expect that this approach will facilitate a systematic development of more complex results in the future, such as categorical approaches to hierarchical exchangeability. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.12840v1-abstract-full').style.display = 'none'; document.getElementById('2411.12840v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 19 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">39 pages</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.12518">arXiv:2411.12518</a> <span> [<a href="https://arxiv.org/pdf/2411.12518">pdf</a>, <a href="https://arxiv.org/format/2411.12518">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="High Energy Physics - Phenomenology">hep-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="High Energy Physics - Experiment">hep-ex</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Accelerator Physics">physics.acc-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Popular Physics">physics.pop-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Quantum Physics">quant-ph</span> </div> </div> <p class="title is-5 mathjax"> Quantum state tomography with muons </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Gao%2C+L">Leyun Gao</a>, <a href="/search/?searchtype=author&query=Ruzi%2C+A">Alim Ruzi</a>, <a href="/search/?searchtype=author&query=Li%2C+Q">Qite Li</a>, <a href="/search/?searchtype=author&query=Zhou%2C+C">Chen Zhou</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Liangwen Chen</a>, <a href="/search/?searchtype=author&query=Zhang%2C+X">Xueheng Zhang</a>, <a href="/search/?searchtype=author&query=Sun%2C+Z">Zhiyu Sun</a>, <a href="/search/?searchtype=author&query=Li%2C+Q">Qiang Li</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.12518v1-abstract-short" style="display: inline;"> Entanglement is a fundamental pillar of quantum mechanics. Probing quantum entanglement and testing Bell inequality with muons can be a significant leap forward, as muon is arguably the only massive elementary particle that can be manipulated and detected over a wide range of energies, e.g., from approximately 0.3 to $10^2$ GeV, corresponding to velocities from 0.94 to nearly the speed of light. I… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.12518v1-abstract-full').style.display = 'inline'; document.getElementById('2411.12518v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.12518v1-abstract-full" style="display: none;"> Entanglement is a fundamental pillar of quantum mechanics. Probing quantum entanglement and testing Bell inequality with muons can be a significant leap forward, as muon is arguably the only massive elementary particle that can be manipulated and detected over a wide range of energies, e.g., from approximately 0.3 to $10^2$ GeV, corresponding to velocities from 0.94 to nearly the speed of light. In this work, we present a realistic proposal and a comprehensive study of quantum entanglement in a state composed of different-flavor fermions in muon-electron scattering. The polarization density matrix for the muon-electron system is derived using a kinematic approach within the relativistic quantum field theory framework. Entanglement in the resulting muon-electron qubit system and the violation of Bell inequalities can be observed with a high event rate. This paves the way for performing quantum tomography with muons. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.12518v1-abstract-full').style.display = 'none'; document.getElementById('2411.12518v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 19 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">6 pages, 3 figures; Probing and Knocking with Muon (PKMu) Experiment Proposal Series 3 for Quantum</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.12426">arXiv:2411.12426</a> <span> [<a href="https://arxiv.org/pdf/2411.12426">pdf</a>, <a href="https://arxiv.org/format/2411.12426">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> </div> </div> <p class="title is-5 mathjax"> Motif Channel Opened in a White-Box: Stereo Matching via Motif Correlation Graph </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Chen%2C+Z">Ziyang Chen</a>, <a href="/search/?searchtype=author&query=Zhang%2C+Y">Yongjun Zhang</a>, <a href="/search/?searchtype=author&query=Li%2C+W">Wenting Li</a>, <a href="/search/?searchtype=author&query=Wang%2C+B">Bingshu Wang</a>, <a href="/search/?searchtype=author&query=Zhao%2C+Y">Yong Zhao</a>, <a href="/search/?searchtype=author&query=Chen%2C+C+L+P">C. L. Philip Chen</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.12426v1-abstract-short" style="display: inline;"> Real-world applications of stereo matching, such as autonomous driving, place stringent demands on both safety and accuracy. However, learning-based stereo matching methods inherently suffer from the loss of geometric structures in certain feature channels, creating a bottleneck in achieving precise detail matching. Additionally, these methods lack interpretability due to the black-box nature of d… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.12426v1-abstract-full').style.display = 'inline'; document.getElementById('2411.12426v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.12426v1-abstract-full" style="display: none;"> Real-world applications of stereo matching, such as autonomous driving, place stringent demands on both safety and accuracy. However, learning-based stereo matching methods inherently suffer from the loss of geometric structures in certain feature channels, creating a bottleneck in achieving precise detail matching. Additionally, these methods lack interpretability due to the black-box nature of deep learning. In this paper, we propose MoCha-V2, a novel learning-based paradigm for stereo matching. MoCha-V2 introduces the Motif Correlation Graph (MCG) to capture recurring textures, which are referred to as ``motifs" within feature channels. These motifs reconstruct geometric structures and are learned in a more interpretable way. Subsequently, we integrate features from multiple frequency domains through wavelet inverse transformation. The resulting motif features are utilized to restore geometric structures in the stereo matching process. Experimental results demonstrate the effectiveness of MoCha-V2. MoCha-V2 achieved 1st place on the Middlebury benchmark at the time of its release. Code is available at https://github.com/ZYangChen/MoCha-Stereo. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.12426v1-abstract-full').style.display = 'none'; document.getElementById('2411.12426v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 19 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.12273">arXiv:2411.12273</a> <span> [<a href="https://arxiv.org/pdf/2411.12273">pdf</a>, <a href="https://arxiv.org/format/2411.12273">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Image and Video Processing">eess.IV</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> </div> </div> <p class="title is-5 mathjax"> Acquire Precise and Comparable Fundus Image Quality Score: FTHNet and FQS Dataset </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Gong%2C+Z">Zheng Gong</a>, <a href="/search/?searchtype=author&query=Deng%2C+Z">Zhuo Deng</a>, <a href="/search/?searchtype=author&query=Gan%2C+R">Run Gan</a>, <a href="/search/?searchtype=author&query=Niu%2C+Z">Zhiyuan Niu</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Lu Chen</a>, <a href="/search/?searchtype=author&query=Huang%2C+C">Canfeng Huang</a>, <a href="/search/?searchtype=author&query=Liang%2C+J">Jia Liang</a>, <a href="/search/?searchtype=author&query=Gao%2C+W">Weihao Gao</a>, <a href="/search/?searchtype=author&query=Li%2C+F">Fang Li</a>, <a href="/search/?searchtype=author&query=Zhang%2C+S">Shaochong Zhang</a>, <a href="/search/?searchtype=author&query=Ma%2C+L">Lan Ma</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.12273v1-abstract-short" style="display: inline;"> The retinal fundus images are utilized extensively in the diagnosis, and their quality can directly affect the diagnosis results. However, due to the insufficient dataset and algorithm application, current fundus image quality assessment (FIQA) methods are not powerful enough to meet ophthalmologists` demands. In this paper, we address the limitations of datasets and algorithms in FIQA. First, we… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.12273v1-abstract-full').style.display = 'inline'; document.getElementById('2411.12273v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.12273v1-abstract-full" style="display: none;"> The retinal fundus images are utilized extensively in the diagnosis, and their quality can directly affect the diagnosis results. However, due to the insufficient dataset and algorithm application, current fundus image quality assessment (FIQA) methods are not powerful enough to meet ophthalmologists` demands. In this paper, we address the limitations of datasets and algorithms in FIQA. First, we establish a new FIQA dataset, Fundus Quality Score(FQS), which includes 2246 fundus images with two labels: a continuous Mean Opinion Score varying from 0 to 100 and a three-level quality label. Then, we propose a FIQA Transformer-based Hypernetwork (FTHNet) to solve these tasks with regression results rather than classification results in conventional FIQA works. The FTHNet is optimized for the FIQA tasks with extensive experiments. Results on our FQS dataset show that the FTHNet can give quality scores for fundus images with PLCC of 0.9423 and SRCC of 0.9488, significantly outperforming other methods with fewer parameters and less computation complexity.We successfully build a dataset and model addressing the problems of current FIQA methods. Furthermore, the model deployment experiments demonstrate its potential in automatic medical image quality control. All experiments are carried out with 10-fold cross-validation to ensure the significance of the results. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.12273v1-abstract-full').style.display = 'none'; document.getElementById('2411.12273v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 19 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">11 pages, 7 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.11915">arXiv:2411.11915</a> <span> [<a href="https://arxiv.org/pdf/2411.11915">pdf</a>, <a href="https://arxiv.org/format/2411.11915">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Genomics">q-bio.GN</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> </div> <p class="title is-5 mathjax"> Phenome-wide causal proteomics enhance systemic lupus erythematosus flare prediction: A study in Asian populations </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Chen%2C+L">Liying Chen</a>, <a href="/search/?searchtype=author&query=Deng%2C+O">Ou Deng</a>, <a href="/search/?searchtype=author&query=Fang%2C+T">Ting Fang</a>, <a href="/search/?searchtype=author&query=Chen%2C+M">Mei Chen</a>, <a href="/search/?searchtype=author&query=Zhang%2C+X">Xvfeng Zhang</a>, <a href="/search/?searchtype=author&query=Cong%2C+R">Ruichen Cong</a>, <a href="/search/?searchtype=author&query=Lu%2C+D">Dingqi Lu</a>, <a href="/search/?searchtype=author&query=Zhang%2C+R">Runrun Zhang</a>, <a href="/search/?searchtype=author&query=Jin%2C+Q">Qun Jin</a>, <a href="/search/?searchtype=author&query=Wang%2C+X">Xinchang Wang</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.11915v1-abstract-short" style="display: inline;"> Objective: Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by unpredictable flares. This study aimed to develop a novel proteomics-based risk prediction model specifically for Asian SLE populations to enhance personalized disease management and early intervention. Methods: A longitudinal cohort study was conducted over 48 weeks, including 139 SLE patients monitored… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.11915v1-abstract-full').style.display = 'inline'; document.getElementById('2411.11915v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.11915v1-abstract-full" style="display: none;"> Objective: Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by unpredictable flares. This study aimed to develop a novel proteomics-based risk prediction model specifically for Asian SLE populations to enhance personalized disease management and early intervention. Methods: A longitudinal cohort study was conducted over 48 weeks, including 139 SLE patients monitored every 12 weeks. Patients were classified into flare (n = 53) and non-flare (n = 86) groups. Baseline plasma samples underwent data-independent acquisition (DIA) proteomics analysis, and phenome-wide Mendelian randomization (PheWAS) was performed to evaluate causal relationships between proteins and clinical predictors. Logistic regression (LR) and random forest (RF) models were used to integrate proteomic and clinical data for flare risk prediction. Results: Five proteins (SAA1, B4GALT5, GIT2, NAA15, and RPIA) were significantly associated with SLE Disease Activity Index-2K (SLEDAI-2K) scores and 1-year flare risk, implicating key pathways such as B-cell receptor signaling and platelet degranulation. SAA1 demonstrated causal effects on flare-related clinical markers, including hemoglobin and red blood cell counts. A combined model integrating clinical and proteomic data achieved the highest predictive accuracy (AUC = 0.769), surpassing individual models. SAA1 was highlighted as a priority biomarker for rapid flare discrimination. Conclusion: The integration of proteomic and clinical data significantly improves flare prediction in Asian SLE patients. The identification of key proteins and their causal relationships with flare-related clinical markers provides valuable insights for proactive SLE management and personalized therapeutic approaches. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.11915v1-abstract-full').style.display = 'none'; document.getElementById('2411.11915v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 17 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.11648">arXiv:2411.11648</a> <span> [<a href="https://arxiv.org/pdf/2411.11648">pdf</a>, <a href="https://arxiv.org/ps/2411.11648">ps</a>, <a href="https://arxiv.org/format/2411.11648">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="High Energy Physics - Experiment">hep-ex</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="High Energy Physics - Phenomenology">hep-ph</span> </div> </div> <p class="title is-5 mathjax"> Evidence for Two Excited $惟^{-}$ Hyperons </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=BESIII+Collaboration"> BESIII Collaboration</a>, <a href="/search/?searchtype=author&query=Ablikim%2C+M">M. Ablikim</a>, <a href="/search/?searchtype=author&query=Achasov%2C+M+N">M. N. Achasov</a>, <a href="/search/?searchtype=author&query=Adlarson%2C+P">P. Adlarson</a>, <a href="/search/?searchtype=author&query=Afedulidis%2C+O">O. Afedulidis</a>, <a href="/search/?searchtype=author&query=Ai%2C+X+C">X. C. Ai</a>, <a href="/search/?searchtype=author&query=Aliberti%2C+R">R. Aliberti</a>, <a href="/search/?searchtype=author&query=Amoroso%2C+A">A. Amoroso</a>, <a href="/search/?searchtype=author&query=Bai%2C+Y">Y. Bai</a>, <a href="/search/?searchtype=author&query=Bakina%2C+O">O. Bakina</a>, <a href="/search/?searchtype=author&query=Balossino%2C+I">I. Balossino</a>, <a href="/search/?searchtype=author&query=Ban%2C+Y">Y. Ban</a>, <a href="/search/?searchtype=author&query=Bao%2C+H+-">H. -R. Bao</a>, <a href="/search/?searchtype=author&query=Batozskaya%2C+V">V. Batozskaya</a>, <a href="/search/?searchtype=author&query=Begzsuren%2C+K">K. Begzsuren</a>, <a href="/search/?searchtype=author&query=Berger%2C+N">N. Berger</a>, <a href="/search/?searchtype=author&query=Berlowski%2C+M">M. Berlowski</a>, <a href="/search/?searchtype=author&query=Bertani%2C+M">M. Bertani</a>, <a href="/search/?searchtype=author&query=Bettoni%2C+D">D. Bettoni</a>, <a href="/search/?searchtype=author&query=Bianchi%2C+F">F. Bianchi</a>, <a href="/search/?searchtype=author&query=Bianco%2C+E">E. Bianco</a>, <a href="/search/?searchtype=author&query=Bortone%2C+A">A. Bortone</a>, <a href="/search/?searchtype=author&query=Boyko%2C+I">I. Boyko</a>, <a href="/search/?searchtype=author&query=Briere%2C+R+A">R. A. Briere</a>, <a href="/search/?searchtype=author&query=Brueggemann%2C+A">A. Brueggemann</a> , et al. (650 additional authors not shown) </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.11648v1-abstract-short" style="display: inline;"> Using $e^+e^-$ collision data corresponding to an integrated luminosity of 19 fb$^{-1}$ collected by the BESIII detector at center-of-mass energies ranging from 4.13 to 4.70 GeV, we report the first evidence for a new excited $惟^{-}$ hyperon, the $惟^*(2109)^{-}$, through the process $e^+ e^- \to 惟^*(2109)^{-} \bar惟^{+} +c.c.$ with a significance of 3.7 $蟽$. The mass and width of $惟^*(2109)^{-}$ ar… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.11648v1-abstract-full').style.display = 'inline'; document.getElementById('2411.11648v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.11648v1-abstract-full" style="display: none;"> Using $e^+e^-$ collision data corresponding to an integrated luminosity of 19 fb$^{-1}$ collected by the BESIII detector at center-of-mass energies ranging from 4.13 to 4.70 GeV, we report the first evidence for a new excited $惟^{-}$ hyperon, the $惟^*(2109)^{-}$, through the process $e^+ e^- \to 惟^*(2109)^{-} \bar惟^{+} +c.c.$ with a significance of 3.7 $蟽$. The mass and width of $惟^*(2109)^{-}$ are measured to be $2108.8 \pm 5.5_{\rm stat} \pm 1.5_{\rm syst} {\rm MeV}/c^{2}$ and $21.6 \pm 17.7_{\rm stat} \pm 9.4_{\rm syst} {\rm MeV}$, respectively. We also present evidence for production of the $惟^*(2012)^{-}$ in the process $e^+ e^- \to 惟^*(2012)^{-} \bar惟^{+} +c.c.$ with a significance of 3.7 $蟽$. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.11648v1-abstract-full').style.display = 'none'; document.getElementById('2411.11648v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 18 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">8 pages, 2 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.11544">arXiv:2411.11544</a> <span> [<a href="https://arxiv.org/pdf/2411.11544">pdf</a>, <a href="https://arxiv.org/ps/2411.11544">ps</a>, <a href="https://arxiv.org/format/2411.11544">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Data Structures and Algorithms">cs.DS</span> </div> </div> <p class="title is-5 mathjax"> The Complexity Landscape of Dynamic Distributed Subgraph Finding </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Chang%2C+Y">Yi-Jun Chang</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Lyuting Chen</a>, <a href="/search/?searchtype=author&query=Chen%2C+Y">Yanyu Chen</a>, <a href="/search/?searchtype=author&query=Mishra%2C+G">Gopinath Mishra</a>, <a href="/search/?searchtype=author&query=Yang%2C+M">Mingyang Yang</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.11544v1-abstract-short" style="display: inline;"> Bonne and Censor-Hillel (ICALP 2019) initiated the study of distributed subgraph finding in dynamic networks of limited bandwidth. For the case where the target subgraph is a clique, they determined the tight bandwidth complexity bounds in nearly all settings. However, several open questions remain, and very little is known about finding subgraphs beyond cliques. In this work, we consider these qu… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.11544v1-abstract-full').style.display = 'inline'; document.getElementById('2411.11544v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.11544v1-abstract-full" style="display: none;"> Bonne and Censor-Hillel (ICALP 2019) initiated the study of distributed subgraph finding in dynamic networks of limited bandwidth. For the case where the target subgraph is a clique, they determined the tight bandwidth complexity bounds in nearly all settings. However, several open questions remain, and very little is known about finding subgraphs beyond cliques. In this work, we consider these questions and explore subgraphs beyond cliques. For finding cliques, we establish an $惟(\log \log n)$ bandwidth lower bound for one-round membership-detection under edge insertions only and an $惟(\log \log \log n)$ bandwidth lower bound for one-round detection under both edge insertions and node insertions. Moreover, we demonstrate new algorithms to show that our lower bounds are tight in bounded-degree networks when the target subgraph is a triangle. Prior to our work, no lower bounds were known for these problems. For finding subgraphs beyond cliques, we present a complete characterization of the bandwidth complexity of the membership-listing problem for every target subgraph, every number of rounds, and every type of topological change: node insertions, node deletions, edge insertions, and edge deletions. We also show partial characterizations for one-round membership-detection and listing. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.11544v1-abstract-full').style.display = 'none'; document.getElementById('2411.11544v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 18 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">37 Pages</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.11490">arXiv:2411.11490</a> <span> [<a href="https://arxiv.org/pdf/2411.11490">pdf</a>, <a href="https://arxiv.org/format/2411.11490">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="High Energy Physics - Theory">hep-th</span> </div> </div> <p class="title is-5 mathjax"> Quantum Fisher information of a cosmic qubit undergoing non-Markovian de Sitter evolution </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Chen%2C+L">Langxuan Chen</a>, <a href="/search/?searchtype=author&query=Feng%2C+J">Jun Feng</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.11490v1-abstract-short" style="display: inline;"> We revisit the problem of thermalization process for an Unruh-DeWitt (UDW) detector in de Sitter space. We derive the full dynamics of the detector in the context of open quantum system, neither using Markovian or RWA approximations. We utilize quantum Fisher information (QFI) for Hubble parameter estimation, as a process function to distinguish the thermalization paths in detector Hilbert space,… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.11490v1-abstract-full').style.display = 'inline'; document.getElementById('2411.11490v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.11490v1-abstract-full" style="display: none;"> We revisit the problem of thermalization process for an Unruh-DeWitt (UDW) detector in de Sitter space. We derive the full dynamics of the detector in the context of open quantum system, neither using Markovian or RWA approximations. We utilize quantum Fisher information (QFI) for Hubble parameter estimation, as a process function to distinguish the thermalization paths in detector Hilbert space, determined by its local properties, e.g., detector energy gap and its initial state preparation, or global spacetime geometry. We find that the non-Markovian contribution in general reduces the QFI comparing with Markovian approximated solution. Regarding to arbitrary initial states, the late-time QFI would converge to an asymptotic value. In particular, we are interested in the background field in the one parameter family of $伪$-vacua in de Sitter space. We show that for general $伪$-vacuum choices, the asymptotic values of converged QFI are significantly suppressed, comparing to previous known results for Bunch-Davies vacuum. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.11490v1-abstract-full').style.display = 'none'; document.getElementById('2411.11490v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 18 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">33 pages, 9 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.11395">arXiv:2411.11395</a> <span> [<a href="https://arxiv.org/pdf/2411.11395">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Materials Science">cond-mat.mtrl-sci</span> </div> </div> <p class="title is-5 mathjax"> Tuneable large nonlinear charge transport driven by the quantum metric at room temperatures in TbMn6Sn6 </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Zhao%2C+W">Weiyao Zhao</a>, <a href="/search/?searchtype=author&query=Xing%2C+K">Kaijian Xing</a>, <a href="/search/?searchtype=author&query=Zhao%2C+Y">Yufei Zhao</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Lei Chen</a>, <a href="/search/?searchtype=author&query=Hong%2C+M">Min Hong</a>, <a href="/search/?searchtype=author&query=Yin%2C+Y">Yuefeng Yin</a>, <a href="/search/?searchtype=author&query=Liu%2C+Y">Yang Liu</a>, <a href="/search/?searchtype=author&query=Le%2C+K+D">Khoa Dang Le</a>, <a href="/search/?searchtype=author&query=Gayles%2C+J">Jacob Gayles</a>, <a href="/search/?searchtype=author&query=Tang%2C+F">Fang Tang</a>, <a href="/search/?searchtype=author&query=Fang%2C+Y">Yong Fang</a>, <a href="/search/?searchtype=author&query=Yan%2C+B">Binghai Yan</a>, <a href="/search/?searchtype=author&query=Karel%2C+J">Julie Karel</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.11395v1-abstract-short" style="display: inline;"> Nonlinear electrodynamics in materials manifests as an electronic response that depends on second- or higher-order powers of the applied electromagnetic field. This response is highly dependent on the underlying crystal symmetries in the material and is typically smaller than the linear responses. Nonlinear responses are therefore usually employed to expose the symmetry breaking, geometric propert… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.11395v1-abstract-full').style.display = 'inline'; document.getElementById('2411.11395v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.11395v1-abstract-full" style="display: none;"> Nonlinear electrodynamics in materials manifests as an electronic response that depends on second- or higher-order powers of the applied electromagnetic field. This response is highly dependent on the underlying crystal symmetries in the material and is typically smaller than the linear responses. Nonlinear responses are therefore usually employed to expose the symmetry breaking, geometric properties of the electronic band structure in materials. Naturally, a material system with a strong nonlinear response is also the key component in nonlinear devices. Here we report the strong room-temperature second-harmonic transport response in a quantum magnet,TbMn6Sn6, which is governed by the quantum metric and can be tuned with applied magnetic fields and temperature. We show that around room temperature, which is close to the spontaneous spin-reorientation transition, the magnetic configurations, and therefore the related symmetry breaking phases, are easily controlled. Our results pave the way from quantum materials to high performance tuneable nonlinear device applications at room temperature. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.11395v1-abstract-full').style.display = 'none'; document.getElementById('2411.11395v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 18 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">12 pages, 3 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.11359">arXiv:2411.11359</a> <span> [<a href="https://arxiv.org/pdf/2411.11359">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Mesoscale and Nanoscale Physics">cond-mat.mes-hall</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Strongly Correlated Electrons">cond-mat.str-el</span> </div> </div> <p class="title is-5 mathjax"> Thickness-dependent Topological Phases and Flat Bands in Rhombohedral Multilayer Graphene </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Xiao%2C+H+B">H. B. Xiao</a>, <a href="/search/?searchtype=author&query=Chen%2C+C">C. Chen</a>, <a href="/search/?searchtype=author&query=Sui%2C+X">X. Sui</a>, <a href="/search/?searchtype=author&query=Zhang%2C+S+H">S. H. Zhang</a>, <a href="/search/?searchtype=author&query=Sun%2C+M+Z">M. Z. Sun</a>, <a href="/search/?searchtype=author&query=Gao%2C+H">H. Gao</a>, <a href="/search/?searchtype=author&query=Jiang%2C+Q">Q. Jiang</a>, <a href="/search/?searchtype=author&query=Li%2C+Q">Q. Li</a>, <a href="/search/?searchtype=author&query=Yang%2C+L+X">L. X. Yang</a>, <a href="/search/?searchtype=author&query=Ye%2C+M">M. Ye</a>, <a href="/search/?searchtype=author&query=Zhu%2C+F+Y">F. Y. Zhu</a>, <a href="/search/?searchtype=author&query=Wang%2C+M+X">M. X. Wang</a>, <a href="/search/?searchtype=author&query=Liu%2C+J+P">J. P. Liu</a>, <a href="/search/?searchtype=author&query=Zhang%2C+Z+B">Z. B. Zhang</a>, <a href="/search/?searchtype=author&query=Wang%2C+Z+J">Z. J. Wang</a>, <a href="/search/?searchtype=author&query=Chen%2C+Y+L">Y. L. Chen</a>, <a href="/search/?searchtype=author&query=Liu%2C+K+H">K. H. Liu</a>, <a href="/search/?searchtype=author&query=Liu%2C+Z+K">Z. K. Liu</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.11359v1-abstract-short" style="display: inline;"> Rhombohedral multilayer graphene has emerged as an extraordinary platform for investigating exotic quantum states, such as superconductivity and fractional quantum anomalous Hall effects, mainly due to the existence of topological surface flatbands. Despite extensive research efforts, a systematic spectroscopic investigation on the evolution of its electronic structure from thin layers to bulk rem… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.11359v1-abstract-full').style.display = 'inline'; document.getElementById('2411.11359v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.11359v1-abstract-full" style="display: none;"> Rhombohedral multilayer graphene has emerged as an extraordinary platform for investigating exotic quantum states, such as superconductivity and fractional quantum anomalous Hall effects, mainly due to the existence of topological surface flatbands. Despite extensive research efforts, a systematic spectroscopic investigation on the evolution of its electronic structure from thin layers to bulk remains elusive. Using state-of-the-art angle-resolved photoemission spectroscopy with submicron spatial resolution, we directly probe and trace the thickness evolution of the topological electronic structures of rhombohedral multilayer graphene. As the layer number increases, the gapped subbands transform into the 3D Dirac nodes that spirals in the momentum space; while the flatbands are constantly observed around Fermi level, and eventually evolve into the topological drumhead surface states. This unique thickness-dependent topological phase transition can be well captured by the 3D generalization of 1D Su-Schrieffer-Heeger chain in thin layers, to the topological Dirac nodal spiral semimetal in the bulk limit. Our findings establish a solid foundation for exploring the exotic quantum phases with nontrivial topology and correlation effects in rhombohedral multilayer graphene. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.11359v1-abstract-full').style.display = 'none'; document.getElementById('2411.11359v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 18 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">15 pages, 4 figures, under review</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.10839">arXiv:2411.10839</a> <span> [<a href="https://arxiv.org/pdf/2411.10839">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Materials Science">cond-mat.mtrl-sci</span> </div> </div> <p class="title is-5 mathjax"> Grain Selection Growth of Soft Metal in Electrochemical Processes </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Zhang%2C+M">Minghao Zhang</a>, <a href="/search/?searchtype=author&query=Tantratian%2C+K">Karnpiwat Tantratian</a>, <a href="/search/?searchtype=author&query=Ham%2C+S">So-Yeon Ham</a>, <a href="/search/?searchtype=author&query=Wang%2C+Z">Zhuo Wang</a>, <a href="/search/?searchtype=author&query=Chouchane%2C+M">Mehdi Chouchane</a>, <a href="/search/?searchtype=author&query=Shimizu%2C+R">Ryosuke Shimizu</a>, <a href="/search/?searchtype=author&query=Bai%2C+S">Shuang Bai</a>, <a href="/search/?searchtype=author&query=Yang%2C+H">Hedi Yang</a>, <a href="/search/?searchtype=author&query=Liu%2C+Z">Zhao Liu</a>, <a href="/search/?searchtype=author&query=Li%2C+L">Letian Li</a>, <a href="/search/?searchtype=author&query=Avishai%2C+A">Amir Avishai</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Lei Chen</a>, <a href="/search/?searchtype=author&query=Meng%2C+Y+S">Ying Shirley Meng</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.10839v1-abstract-short" style="display: inline;"> Soft metals like lithium and sodium play a critical role in battery technology owing to their high energy density. Texture formation by grain selection growth of soft metals during electrochemical processes is a crucial factor affecting power and safety. Developing a framework to understand and control grain growth is a multifaceted challenge. Here, a general thermodynamic theory and phase-field m… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.10839v1-abstract-full').style.display = 'inline'; document.getElementById('2411.10839v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.10839v1-abstract-full" style="display: none;"> Soft metals like lithium and sodium play a critical role in battery technology owing to their high energy density. Texture formation by grain selection growth of soft metals during electrochemical processes is a crucial factor affecting power and safety. Developing a framework to understand and control grain growth is a multifaceted challenge. Here, a general thermodynamic theory and phase-field model are formulated to study grain selection growth of soft metals. Our study focuses on the interplay between surface energy and atomic mobility-related intrinsic strain energy in grain selection growth. Differences in grain selection growth arise from the anisotropy in surface energy and diffusion barrier of soft metal atoms. Our findings highlight the kinetic limitations of solid-state Li metal batteries, which originate from load stress-induced surface energy anisotropy. These insights lead to the development of an amorphous LixSi1-x (0.50<x<0.79) seed layer, improving the critical current density at room temperature for anode-free Li solid-state batteries through the control of grain selection growth. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.10839v1-abstract-full').style.display = 'none'; document.getElementById('2411.10839v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 16 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.10396">arXiv:2411.10396</a> <span> [<a href="https://arxiv.org/pdf/2411.10396">pdf</a>, <a href="https://arxiv.org/format/2411.10396">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Quantum Physics">quant-ph</span> </div> </div> <p class="title is-5 mathjax"> Implementation of scalable suspended superinductors </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=J%C3%BCnger%2C+C">Christian J眉nger</a>, <a href="/search/?searchtype=author&query=Chistolini%2C+T">Trevor Chistolini</a>, <a href="/search/?searchtype=author&query=Nguyen%2C+L+B">Long B. Nguyen</a>, <a href="/search/?searchtype=author&query=Kim%2C+H">Hyunseong Kim</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Larry Chen</a>, <a href="/search/?searchtype=author&query=Ersevim%2C+T">Thomas Ersevim</a>, <a href="/search/?searchtype=author&query=Livingston%2C+W">William Livingston</a>, <a href="/search/?searchtype=author&query=Koolstra%2C+G">Gerwin Koolstra</a>, <a href="/search/?searchtype=author&query=Santiago%2C+D+I">David I. Santiago</a>, <a href="/search/?searchtype=author&query=Siddiqi%2C+I">Irfan Siddiqi</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.10396v1-abstract-short" style="display: inline;"> Superinductors have become a crucial component in the superconducting circuit toolbox, playing a key role in the development of more robust qubits. Enhancing the performance of these devices can be achieved by suspending the superinductors from the substrate, thereby reducing stray capacitance. Here, we present a fabrication framework for constructing superconducting circuits with suspended superi… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.10396v1-abstract-full').style.display = 'inline'; document.getElementById('2411.10396v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.10396v1-abstract-full" style="display: none;"> Superinductors have become a crucial component in the superconducting circuit toolbox, playing a key role in the development of more robust qubits. Enhancing the performance of these devices can be achieved by suspending the superinductors from the substrate, thereby reducing stray capacitance. Here, we present a fabrication framework for constructing superconducting circuits with suspended superinductors in planar architectures. To validate the effectiveness of this process, we systematically characterize both resonators and qubits with suspended arrays of Josephson junctions, ultimately confirming the high quality of the superinductive elements. In addition, this process is broadly compatible with other types of superinductors and circuit designs. Our results not only pave the way for scalable novel superconducting architectures but also provide the primitive for future investigation of loss mechanisms associated with the device substrate. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.10396v1-abstract-full').style.display = 'none'; document.getElementById('2411.10396v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 15 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.09852">arXiv:2411.09852</a> <span> [<a href="https://arxiv.org/pdf/2411.09852">pdf</a>, <a href="https://arxiv.org/format/2411.09852">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Retrieval">cs.IR</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> </div> <p class="title is-5 mathjax"> InterFormer: Towards Effective Heterogeneous Interaction Learning for Click-Through Rate Prediction </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Zeng%2C+Z">Zhichen Zeng</a>, <a href="/search/?searchtype=author&query=Liu%2C+X">Xiaolong Liu</a>, <a href="/search/?searchtype=author&query=Hang%2C+M">Mengyue Hang</a>, <a href="/search/?searchtype=author&query=Liu%2C+X">Xiaoyi Liu</a>, <a href="/search/?searchtype=author&query=Zhou%2C+Q">Qinghai Zhou</a>, <a href="/search/?searchtype=author&query=Yang%2C+C">Chaofei Yang</a>, <a href="/search/?searchtype=author&query=Liu%2C+Y">Yiqun Liu</a>, <a href="/search/?searchtype=author&query=Ruan%2C+Y">Yichen Ruan</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Laming Chen</a>, <a href="/search/?searchtype=author&query=Chen%2C+Y">Yuxin Chen</a>, <a href="/search/?searchtype=author&query=Hao%2C+Y">Yujia Hao</a>, <a href="/search/?searchtype=author&query=Xu%2C+J">Jiaqi Xu</a>, <a href="/search/?searchtype=author&query=Nie%2C+J">Jade Nie</a>, <a href="/search/?searchtype=author&query=Liu%2C+X">Xi Liu</a>, <a href="/search/?searchtype=author&query=Zhang%2C+B">Buyun Zhang</a>, <a href="/search/?searchtype=author&query=Wen%2C+W">Wei Wen</a>, <a href="/search/?searchtype=author&query=Yuan%2C+S">Siyang Yuan</a>, <a href="/search/?searchtype=author&query=Wang%2C+K">Kai Wang</a>, <a href="/search/?searchtype=author&query=Chen%2C+W">Wen-Yen Chen</a>, <a href="/search/?searchtype=author&query=Han%2C+Y">Yiping Han</a>, <a href="/search/?searchtype=author&query=Li%2C+H">Huayu Li</a>, <a href="/search/?searchtype=author&query=Yang%2C+C">Chunzhi Yang</a>, <a href="/search/?searchtype=author&query=Long%2C+B">Bo Long</a>, <a href="/search/?searchtype=author&query=Yu%2C+P+S">Philip S. Yu</a>, <a href="/search/?searchtype=author&query=Tong%2C+H">Hanghang Tong</a> , et al. (1 additional authors not shown) </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.09852v1-abstract-short" style="display: inline;"> Click-through rate (CTR) prediction, which predicts the probability of a user clicking an ad, is a fundamental task in recommender systems. The emergence of heterogeneous information, such as user profile and behavior sequences, depicts user interests from different aspects. A mutually beneficial integration of heterogeneous information is the cornerstone towards the success of CTR prediction. How… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.09852v1-abstract-full').style.display = 'inline'; document.getElementById('2411.09852v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.09852v1-abstract-full" style="display: none;"> Click-through rate (CTR) prediction, which predicts the probability of a user clicking an ad, is a fundamental task in recommender systems. The emergence of heterogeneous information, such as user profile and behavior sequences, depicts user interests from different aspects. A mutually beneficial integration of heterogeneous information is the cornerstone towards the success of CTR prediction. However, most of the existing methods suffer from two fundamental limitations, including (1) insufficient inter-mode interaction due to the unidirectional information flow between modes, and (2) aggressive information aggregation caused by early summarization, resulting in excessive information loss. To address the above limitations, we propose a novel module named InterFormer to learn heterogeneous information interaction in an interleaving style. To achieve better interaction learning, InterFormer enables bidirectional information flow for mutually beneficial learning across different modes. To avoid aggressive information aggregation, we retain complete information in each data mode and use a separate bridging arch for effective information selection and summarization. Our proposed InterFormer achieves state-of-the-art performance on three public datasets and a large-scale industrial dataset. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.09852v1-abstract-full').style.display = 'none'; document.getElementById('2411.09852v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 14 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">10 pages, 6 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.09697">arXiv:2411.09697</a> <span> [<a href="https://arxiv.org/pdf/2411.09697">pdf</a>, <a href="https://arxiv.org/format/2411.09697">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Quantum Physics">quant-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Strongly Correlated Electrons">cond-mat.str-el</span> </div> </div> <p class="title is-5 mathjax"> A Universal Circuit Set Using the $S_3$ Quantum Double </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Chen%2C+L">Liyuan Chen</a>, <a href="/search/?searchtype=author&query=Ren%2C+Y">Yuanjie Ren</a>, <a href="/search/?searchtype=author&query=Fan%2C+R">Ruihua Fan</a>, <a href="/search/?searchtype=author&query=Jaffe%2C+A">Arthur Jaffe</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.09697v1-abstract-short" style="display: inline;"> One potential route toward fault-tolerant universal quantum computation is to use non-Abelian topological codes. In this work, we investigate how to achieve this goal with the quantum double model $\mathcal{D}(S_3)$ -- a specific non-Abelian topological code. By embedding each on-site Hilbert space into a qubit-qutrit pair, we give an explicit construction of the circuits for creating, moving, and… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.09697v1-abstract-full').style.display = 'inline'; document.getElementById('2411.09697v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.09697v1-abstract-full" style="display: none;"> One potential route toward fault-tolerant universal quantum computation is to use non-Abelian topological codes. In this work, we investigate how to achieve this goal with the quantum double model $\mathcal{D}(S_3)$ -- a specific non-Abelian topological code. By embedding each on-site Hilbert space into a qubit-qutrit pair, we give an explicit construction of the circuits for creating, moving, and locally measuring all non-trivial anyons. We also design a specialized anyon interferometer to measure the total charge remotely for well-separated anyons; this avoids fusing them together. These protocols enable the implementation of a universal gate set proposed by Cui et al. and active quantum error correction of the circuit-level noise during the computation process. To further reduce the error rate and facilitate error correction, we encode each physical degree of freedom of $\mathcal{D}(S_3)$ into a novel, quantum, error-correcting code, enabling fault-tolerant realization, at the logical level, of all gates in the anyon manipulation circuits. Our proposal offers a promising path to realize universal topological quantum computation in the NISQ era. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.09697v1-abstract-full').style.display = 'none'; document.getElementById('2411.09697v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 14 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">17 pages</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.08302">arXiv:2411.08302</a> <span> [<a href="https://arxiv.org/pdf/2411.08302">pdf</a>, <a href="https://arxiv.org/format/2411.08302">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> </div> </div> <p class="title is-5 mathjax"> R3HF: Reward Redistribution for Enhancing Reinforcement Learning from Human Feedback </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Li%2C+J">Jiahui Li</a>, <a href="/search/?searchtype=author&query=Chang%2C+T">Tai-wei Chang</a>, <a href="/search/?searchtype=author&query=Zhang%2C+F">Fengda Zhang</a>, <a href="/search/?searchtype=author&query=Kuang%2C+K">Kun Kuang</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Long Chen</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.08302v1-abstract-short" style="display: inline;"> Reinforcement learning from human feedback (RLHF) provides a paradigm for aligning large language models (LLMs) with human preferences. This involves the initial training of a reward model based on pairwise human feedback. The reward model is subsequently utilized in reinforcement learning to assess the scores of each generated sentence as a whole, further guiding the optimization of LLMs. However… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.08302v1-abstract-full').style.display = 'inline'; document.getElementById('2411.08302v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.08302v1-abstract-full" style="display: none;"> Reinforcement learning from human feedback (RLHF) provides a paradigm for aligning large language models (LLMs) with human preferences. This involves the initial training of a reward model based on pairwise human feedback. The reward model is subsequently utilized in reinforcement learning to assess the scores of each generated sentence as a whole, further guiding the optimization of LLMs. However, current approaches have a significant shortcoming: \emph{They allocate a single, sparse, and delayed reward to an entire sequence of output}. This may overlook some significant individual contributions of each token towards the desired outcome. To overcome this limitation, our paper proposes a novel reward redistribution method called R3HF, which facilitates a more fine-grained, token-level reward allocation. Specifically, our method treats the reward prediction task of the reward model as a regression problem. As a result, the redistributed rewards are computed by evaluating the specific contribution of each token to the reward model's output. This detailed approach improves the model's understanding of language nuances, leading to more precise enhancements in its performance. Our method is crafted to integrate seamlessly with most current techniques while incurring minimal computational costs. Through comprehensive experiments across diverse datasets and tasks, we have verified the effectiveness and superiority of our approach. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.08302v1-abstract-full').style.display = 'none'; document.getElementById('2411.08302v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 12 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.07886">arXiv:2411.07886</a> <span> [<a href="https://arxiv.org/pdf/2411.07886">pdf</a>, <a href="https://arxiv.org/format/2411.07886">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Quantum Physics">quant-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Chemical Physics">physics.chem-ph</span> </div> </div> <p class="title is-5 mathjax"> Simulating Quantum Many-Body States with Neural-Network Exponential Ansatz </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Zeng%2C+W">Weillei Zeng</a>, <a href="/search/?searchtype=author&query=Zhang%2C+J">Jiaji Zhang</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Lipeng Chen</a>, <a href="/search/?searchtype=author&query=Benavides-Riveros%2C+C+L">Carlos L. Benavides-Riveros</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.07886v1-abstract-short" style="display: inline;"> Preparing quantum many-body states on classical or quantum devices is a very challenging task that requires accounting for exponentially large Hilbert spaces. Although this complexity can be managed with exponential ans盲tze (such as in the coupled-cluster method), these approaches are often tailored to specific systems, which limits their universality. Recent work has shown that the contracted Sch… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.07886v1-abstract-full').style.display = 'inline'; document.getElementById('2411.07886v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.07886v1-abstract-full" style="display: none;"> Preparing quantum many-body states on classical or quantum devices is a very challenging task that requires accounting for exponentially large Hilbert spaces. Although this complexity can be managed with exponential ans盲tze (such as in the coupled-cluster method), these approaches are often tailored to specific systems, which limits their universality. Recent work has shown that the contracted Schr枚dinger equation enables the construction of universal, formally exact exponential ans盲tze for quantum many-body physics. However, while the ansatz is capable of resolving arbitrary quantum systems, it still requires a full calculation of its parameters whenever the underlying Hamiltonian changes, even slightly. Here, inspired by recent progress in operator learning, we develop a surrogate neural network solver that generates the exponential ansatz parameters using the Hamiltonian parameters as inputs, eliminating the need for repetitive computations. We illustrate the effectiveness of this approach by training neural networks of several quantum many-body systems, including the Fermi-Hubbard model. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.07886v1-abstract-full').style.display = 'none'; document.getElementById('2411.07886v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 12 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">9 pages, 6 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.07843">arXiv:2411.07843</a> <span> [<a href="https://arxiv.org/pdf/2411.07843">pdf</a>, <a href="https://arxiv.org/format/2411.07843">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> </div> </div> <p class="title is-5 mathjax"> Chain Association-based Attacking and Shielding Natural Language Processing Systems </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Huang%2C+J">Jiacheng Huang</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Long Chen</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.07843v1-abstract-short" style="display: inline;"> Association as a gift enables people do not have to mention something in completely straightforward words and allows others to understand what they intend to refer to. In this paper, we propose a chain association-based adversarial attack against natural language processing systems, utilizing the comprehension gap between humans and machines. We first generate a chain association graph for Chinese… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.07843v1-abstract-full').style.display = 'inline'; document.getElementById('2411.07843v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.07843v1-abstract-full" style="display: none;"> Association as a gift enables people do not have to mention something in completely straightforward words and allows others to understand what they intend to refer to. In this paper, we propose a chain association-based adversarial attack against natural language processing systems, utilizing the comprehension gap between humans and machines. We first generate a chain association graph for Chinese characters based on the association paradigm for building search space of potential adversarial examples. Then, we introduce an discrete particle swarm optimization algorithm to search for the optimal adversarial examples. We conduct comprehensive experiments and show that advanced natural language processing models and applications, including large language models, are vulnerable to our attack, while humans appear good at understanding the perturbed text. We also explore two methods, including adversarial training and associative graph-based recovery, to shield systems from chain association-based attack. Since a few examples that use some derogatory terms, this paper contains materials that may be offensive or upsetting to some people. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.07843v1-abstract-full').style.display = 'none'; document.getElementById('2411.07843v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 12 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.07730">arXiv:2411.07730</a> <span> [<a href="https://arxiv.org/pdf/2411.07730">pdf</a>, <a href="https://arxiv.org/ps/2411.07730">ps</a>, <a href="https://arxiv.org/format/2411.07730">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="High Energy Physics - Experiment">hep-ex</span> </div> </div> <p class="title is-5 mathjax"> Study of the light scalar $a_{0}(980)$ through the decay $D^{0} \to a_{0}(980)^-e^{+} 谓_{e}$ with $a_{0}(980)^- \to 畏蟺^-$ </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=BESIII+Collaboration"> BESIII Collaboration</a>, <a href="/search/?searchtype=author&query=Ablikim%2C+M">M. Ablikim</a>, <a href="/search/?searchtype=author&query=Achasov%2C+M+N">M. N. Achasov</a>, <a href="/search/?searchtype=author&query=Adlarson%2C+P">P. Adlarson</a>, <a href="/search/?searchtype=author&query=Afedulidis%2C+O">O. Afedulidis</a>, <a href="/search/?searchtype=author&query=Ai%2C+X+C">X. C. Ai</a>, <a href="/search/?searchtype=author&query=Aliberti%2C+R">R. Aliberti</a>, <a href="/search/?searchtype=author&query=Amoroso%2C+A">A. Amoroso</a>, <a href="/search/?searchtype=author&query=An%2C+Q">Q. An</a>, <a href="/search/?searchtype=author&query=Bai%2C+Y">Y. Bai</a>, <a href="/search/?searchtype=author&query=Bakina%2C+O">O. Bakina</a>, <a href="/search/?searchtype=author&query=Balossino%2C+I">I. Balossino</a>, <a href="/search/?searchtype=author&query=Ban%2C+Y">Y. Ban</a>, <a href="/search/?searchtype=author&query=Bao%2C+H+-">H. -R. Bao</a>, <a href="/search/?searchtype=author&query=Batozskaya%2C+V">V. Batozskaya</a>, <a href="/search/?searchtype=author&query=Begzsuren%2C+K">K. Begzsuren</a>, <a href="/search/?searchtype=author&query=Berger%2C+N">N. Berger</a>, <a href="/search/?searchtype=author&query=Berlowski%2C+M">M. Berlowski</a>, <a href="/search/?searchtype=author&query=Bertani%2C+M">M. Bertani</a>, <a href="/search/?searchtype=author&query=Bettoni%2C+D">D. Bettoni</a>, <a href="/search/?searchtype=author&query=Bianchi%2C+F">F. Bianchi</a>, <a href="/search/?searchtype=author&query=Bianco%2C+E">E. Bianco</a>, <a href="/search/?searchtype=author&query=Bortone%2C+A">A. Bortone</a>, <a href="/search/?searchtype=author&query=Boyko%2C+I">I. Boyko</a>, <a href="/search/?searchtype=author&query=Briere%2C+R+A">R. A. Briere</a> , et al. (649 additional authors not shown) </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.07730v1-abstract-short" style="display: inline;"> Using 7.93 ${\rm fb^{-1}}$ of $e^+e^-$ collision data collected at a center-of-mass energy of 3.773 ${\rm GeV}$ with the BESIII detector, we present an analysis of the decay $D^{0} \to 畏蟺^- e^+ 谓_{e}$. The branching fraction of the decay $D^{0} \to a_{0}(980)^{-} e^+ 谓_{e}$ with $a_{0}(980)^{-} \to 畏蟺^{-}$ is measured to be $(0.86\pm0.17_{\text{stat}}\pm0.05_{\text{syst}})\times 10^{-4}$. The deca… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.07730v1-abstract-full').style.display = 'inline'; document.getElementById('2411.07730v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.07730v1-abstract-full" style="display: none;"> Using 7.93 ${\rm fb^{-1}}$ of $e^+e^-$ collision data collected at a center-of-mass energy of 3.773 ${\rm GeV}$ with the BESIII detector, we present an analysis of the decay $D^{0} \to 畏蟺^- e^+ 谓_{e}$. The branching fraction of the decay $D^{0} \to a_{0}(980)^{-} e^+ 谓_{e}$ with $a_{0}(980)^{-} \to 畏蟺^{-}$ is measured to be $(0.86\pm0.17_{\text{stat}}\pm0.05_{\text{syst}})\times 10^{-4}$. The decay dynamics of this process is studied with a single-pole parameterization of the hadronic form factor and the Flatt茅 formula describing the $a_0(980)$ line shape in the differential decay rate. The product of the form factor $f^{ a_0}_{+}(0)$ and the Cabibbo-Kobayashi-Maskawa matrix element $|V_{cd}|$ is determined for the first time with the result $f^{ a_0}_+(0)|V_{cd}|=0.126\pm0.013_{\rm stat}\pm0.003_{\rm syst}$. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.07730v1-abstract-full').style.display = 'none'; document.getElementById('2411.07730v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 12 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.07672">arXiv:2411.07672</a> <span> [<a href="https://arxiv.org/pdf/2411.07672">pdf</a>, <a href="https://arxiv.org/format/2411.07672">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> </div> <p class="title is-5 mathjax"> Rethinking Structure Learning For Graph Neural Networks </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Zheng%2C+Y">Yilun Zheng</a>, <a href="/search/?searchtype=author&query=Zhang%2C+Z">Zhuofan Zhang</a>, <a href="/search/?searchtype=author&query=Wang%2C+Z">Ziming Wang</a>, <a href="/search/?searchtype=author&query=Li%2C+X">Xiang Li</a>, <a href="/search/?searchtype=author&query=Luan%2C+S">Sitao Luan</a>, <a href="/search/?searchtype=author&query=Peng%2C+X">Xiaojiang Peng</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Lihui Chen</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.07672v1-abstract-short" style="display: inline;"> To improve the performance of Graph Neural Networks (GNNs), Graph Structure Learning (GSL) has been extensively applied to reconstruct or refine original graph structures, effectively addressing issues like heterophily, over-squashing, and noisy structures. While GSL is generally thought to improve GNN performance, it often leads to longer training times and more hyperparameter tuning. Besides, th… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.07672v1-abstract-full').style.display = 'inline'; document.getElementById('2411.07672v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.07672v1-abstract-full" style="display: none;"> To improve the performance of Graph Neural Networks (GNNs), Graph Structure Learning (GSL) has been extensively applied to reconstruct or refine original graph structures, effectively addressing issues like heterophily, over-squashing, and noisy structures. While GSL is generally thought to improve GNN performance, it often leads to longer training times and more hyperparameter tuning. Besides, the distinctions among current GSL methods remain ambiguous from the perspective of GNN training, and there is a lack of theoretical analysis to quantify their effectiveness. Recent studies further suggest that, under fair comparisons with the same hyperparameter tuning, GSL does not consistently outperform baseline GNNs. This motivates us to ask a critical question: is GSL really useful for GNNs? To address this question, this paper makes two key contributions. First, we propose a new GSL framework, which includes three steps: GSL base (the representation used for GSL) construction, new structure construction, and view fusion, to better understand the effectiveness of GSL in GNNs. Second, after graph convolution, we analyze the differences in mutual information (MI) between node representations derived from the original topology and those from the newly constructed topology. Surprisingly, our empirical observations and theoretical analysis show that no matter which type of graph structure construction methods are used, after feeding the same GSL bases to the newly constructed graph, there is no MI gain compared to the original GSL bases. To fairly reassess the effectiveness of GSL, we conduct ablation experiments and find that it is the pretrained GSL bases that enhance GNN performance, and in most cases, GSL cannot improve GNN performance. This finding encourages us to rethink the essential components in GNNs, such as self-training and structural encoding, in GNN design rather than GSL. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.07672v1-abstract-full').style.display = 'none'; document.getElementById('2411.07672v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 12 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.07663">arXiv:2411.07663</a> <span> [<a href="https://arxiv.org/pdf/2411.07663">pdf</a>, <a href="https://arxiv.org/format/2411.07663">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Social and Information Networks">cs.SI</span> </div> </div> <p class="title is-5 mathjax"> Is Graph Convolution Always Beneficial For Every Feature? </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Zheng%2C+Y">Yilun Zheng</a>, <a href="/search/?searchtype=author&query=Li%2C+X">Xiang Li</a>, <a href="/search/?searchtype=author&query=Luan%2C+S">Sitao Luan</a>, <a href="/search/?searchtype=author&query=Peng%2C+X">Xiaojiang Peng</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Lihui Chen</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.07663v1-abstract-short" style="display: inline;"> Graph Neural Networks (GNNs) have demonstrated strong capabilities in processing structured data. While traditional GNNs typically treat each feature dimension equally during graph convolution, we raise an important question: Is the graph convolution operation equally beneficial for each feature? If not, the convolution operation on certain feature dimensions can possibly lead to harmful effects,… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.07663v1-abstract-full').style.display = 'inline'; document.getElementById('2411.07663v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.07663v1-abstract-full" style="display: none;"> Graph Neural Networks (GNNs) have demonstrated strong capabilities in processing structured data. While traditional GNNs typically treat each feature dimension equally during graph convolution, we raise an important question: Is the graph convolution operation equally beneficial for each feature? If not, the convolution operation on certain feature dimensions can possibly lead to harmful effects, even worse than the convolution-free models. In prior studies, to assess the impacts of graph convolution on features, people proposed metrics based on feature homophily to measure feature consistency with the graph topology. However, these metrics have shown unsatisfactory alignment with GNN performance and have not been effectively employed to guide feature selection in GNNs. To address these limitations, we introduce a novel metric, Topological Feature Informativeness (TFI), to distinguish between GNN-favored and GNN-disfavored features, where its effectiveness is validated through both theoretical analysis and empirical observations. Based on TFI, we propose a simple yet effective Graph Feature Selection (GFS) method, which processes GNN-favored and GNN-disfavored features separately, using GNNs and non-GNN models. Compared to original GNNs, GFS significantly improves the extraction of useful topological information from each feature with comparable computational costs. Extensive experiments show that after applying GFS to 8 baseline and state-of-the-art (SOTA) GNN architectures across 10 datasets, 83.75% of the GFS-augmented cases show significant performance boosts. Furthermore, our proposed TFI metric outperforms other feature selection methods. These results validate the effectiveness of both GFS and TFI. Additionally, we demonstrate that GFS's improvements are robust to hyperparameter tuning, highlighting its potential as a universal method for enhancing various GNN architectures. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.07663v1-abstract-full').style.display = 'none'; document.getElementById('2411.07663v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 12 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.07025">arXiv:2411.07025</a> <span> [<a href="https://arxiv.org/pdf/2411.07025">pdf</a>, <a href="https://arxiv.org/format/2411.07025">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Graphics">cs.GR</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> </div> </div> <p class="title is-5 mathjax"> Scaling Mesh Generation via Compressive Tokenization </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Weng%2C+H">Haohan Weng</a>, <a href="/search/?searchtype=author&query=Zhao%2C+Z">Zibo Zhao</a>, <a href="/search/?searchtype=author&query=Lei%2C+B">Biwen Lei</a>, <a href="/search/?searchtype=author&query=Yang%2C+X">Xianghui Yang</a>, <a href="/search/?searchtype=author&query=Liu%2C+J">Jian Liu</a>, <a href="/search/?searchtype=author&query=Lai%2C+Z">Zeqiang Lai</a>, <a href="/search/?searchtype=author&query=Chen%2C+Z">Zhuo Chen</a>, <a href="/search/?searchtype=author&query=Liu%2C+Y">Yuhong Liu</a>, <a href="/search/?searchtype=author&query=Jiang%2C+J">Jie Jiang</a>, <a href="/search/?searchtype=author&query=Guo%2C+C">Chunchao Guo</a>, <a href="/search/?searchtype=author&query=Zhang%2C+T">Tong Zhang</a>, <a href="/search/?searchtype=author&query=Gao%2C+S">Shenghua Gao</a>, <a href="/search/?searchtype=author&query=Chen%2C+C+L+P">C. L. Philip Chen</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.07025v1-abstract-short" style="display: inline;"> We propose a compressive yet effective mesh representation, Blocked and Patchified Tokenization (BPT), facilitating the generation of meshes exceeding 8k faces. BPT compresses mesh sequences by employing block-wise indexing and patch aggregation, reducing their length by approximately 75\% compared to the original sequences. This compression milestone unlocks the potential to utilize mesh data wit… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.07025v1-abstract-full').style.display = 'inline'; document.getElementById('2411.07025v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.07025v1-abstract-full" style="display: none;"> We propose a compressive yet effective mesh representation, Blocked and Patchified Tokenization (BPT), facilitating the generation of meshes exceeding 8k faces. BPT compresses mesh sequences by employing block-wise indexing and patch aggregation, reducing their length by approximately 75\% compared to the original sequences. This compression milestone unlocks the potential to utilize mesh data with significantly more faces, thereby enhancing detail richness and improving generation robustness. Empowered with the BPT, we have built a foundation mesh generative model training on scaled mesh data to support flexible control for point clouds and images. Our model demonstrates the capability to generate meshes with intricate details and accurate topology, achieving SoTA performance on mesh generation and reaching the level for direct product usage. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.07025v1-abstract-full').style.display = 'none'; document.getElementById('2411.07025v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 11 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Homepage: https://whaohan.github.io/bpt , Code: https://github.com/whaohan/bpt</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.06975">arXiv:2411.06975</a> <span> [<a href="https://arxiv.org/pdf/2411.06975">pdf</a>, <a href="https://arxiv.org/format/2411.06975">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="General Relativity and Quantum Cosmology">gr-qc</span> </div> </div> <p class="title is-5 mathjax"> Comment on "Attractor solutions in scalar-field cosmology" and "How many e-folds should we expect from high-scale inflation?" </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Han%2C+Y">Yu Han</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Long Chen</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.06975v1-abstract-short" style="display: inline;"> It was claimed in Ref.[1] that in the spatially flat cosmological case there exists a unique conserved measure (up to normalization) on the effective phase space $(蠁,\dot蠁)$ for scalar-field with $m^2蠁^2$ potential through the proof of the existence of a unique solution to the differential equation $(44)$ with a unique physical solution in the low-energy limit. Moreover, in Ref.[2] it was also cla… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.06975v1-abstract-full').style.display = 'inline'; document.getElementById('2411.06975v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.06975v1-abstract-full" style="display: none;"> It was claimed in Ref.[1] that in the spatially flat cosmological case there exists a unique conserved measure (up to normalization) on the effective phase space $(蠁,\dot蠁)$ for scalar-field with $m^2蠁^2$ potential through the proof of the existence of a unique solution to the differential equation $(44)$ with a unique physical solution in the low-energy limit. Moreover, in Ref.[2] it was also claimed that a unique physical solution to the same differential equation was found in the high-energy limit. In this comment, we reexamine these claims. We obtain general physical solutions to the equation $(44)$ both in the low-energy and high-energy limit, which include the asymptotic solutions in Ref.[1] and Ref.[2] as special cases. Therefore, we conclude that following the constructions in Ref.[1] there actually exist infinitely many conserved measures for the scalar-field with $m^2蠁^2$ potential. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.06975v1-abstract-full').style.display = 'none'; document.getElementById('2411.06975v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 11 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">4 pages,3 captioned figures, Comment on arXiv:1309.2611 [gr-qc] and arXiv:1405.5538 [hep-th]</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.06476">arXiv:2411.06476</a> <span> [<a href="https://arxiv.org/pdf/2411.06476">pdf</a>, <a href="https://arxiv.org/format/2411.06476">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Numerical Analysis">math.NA</span> </div> </div> <p class="title is-5 mathjax"> Eigen-componentwise convergence of SGD for quadratic programming </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Chen%2C+L">Lehan Chen</a>, <a href="/search/?searchtype=author&query=Nakatsukasa%2C+Y">Yuji Nakatsukasa</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.06476v1-abstract-short" style="display: inline;"> Stochastic gradient descent (SGD) is a workhorse algorithm for solving large-scale optimization problems in data science and machine learning. Understanding the convergence of SGD is hence of fundamental importance. In this work we examine the SGD convergence (with various step sizes) when applied to unconstrained convex quadratic programming (essentially least-squares (LS) problems), and in parti… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.06476v1-abstract-full').style.display = 'inline'; document.getElementById('2411.06476v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.06476v1-abstract-full" style="display: none;"> Stochastic gradient descent (SGD) is a workhorse algorithm for solving large-scale optimization problems in data science and machine learning. Understanding the convergence of SGD is hence of fundamental importance. In this work we examine the SGD convergence (with various step sizes) when applied to unconstrained convex quadratic programming (essentially least-squares (LS) problems), and in particular analyze the error components respect to the eigenvectors of the Hessian. The main message is that the convergence depends largely on the corresponding eigenvalues (singular values of the coefficient matrix in the LS context), namely the components for the large singular values converge faster in the initial phase. We then show there is a phase transition in the convergence where the convergence speed of the components, especially those corresponding to the larger singular values, will decrease. Finally, we show that the convergence of the overall error (in the solution) tends to decay as more iterations are run, that is, the initial convergence is faster than the asymptote. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.06476v1-abstract-full').style.display = 'none'; document.getElementById('2411.06476v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 10 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.06213">arXiv:2411.06213</a> <span> [<a href="https://arxiv.org/pdf/2411.06213">pdf</a>, <a href="https://arxiv.org/ps/2411.06213">ps</a>, <a href="https://arxiv.org/format/2411.06213">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> </div> </div> <p class="title is-5 mathjax"> Incorporating Human Explanations for Robust Hate Speech Detection </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Chen%2C+J+L">Jennifer L. Chen</a>, <a href="/search/?searchtype=author&query=Ladhak%2C+F">Faisal Ladhak</a>, <a href="/search/?searchtype=author&query=Li%2C+D">Daniel Li</a>, <a href="/search/?searchtype=author&query=Elhadad%2C+N">No茅mie Elhadad</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.06213v1-abstract-short" style="display: inline;"> Given the black-box nature and complexity of large transformer language models (LM), concerns about generalizability and robustness present ethical implications for domains such as hate speech (HS) detection. Using the content rich Social Bias Frames dataset, containing human-annotated stereotypes, intent, and targeted groups, we develop a three stage analysis to evaluate if LMs faithfully assess… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.06213v1-abstract-full').style.display = 'inline'; document.getElementById('2411.06213v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.06213v1-abstract-full" style="display: none;"> Given the black-box nature and complexity of large transformer language models (LM), concerns about generalizability and robustness present ethical implications for domains such as hate speech (HS) detection. Using the content rich Social Bias Frames dataset, containing human-annotated stereotypes, intent, and targeted groups, we develop a three stage analysis to evaluate if LMs faithfully assess hate speech. First, we observe the need for modeling contextually grounded stereotype intents to capture implicit semantic meaning. Next, we design a new task, Stereotype Intent Entailment (SIE), which encourages a model to contextually understand stereotype presence. Finally, through ablation tests and user studies, we find a SIE objective improves content understanding, but challenges remain in modeling implicit intent. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.06213v1-abstract-full').style.display = 'none'; document.getElementById('2411.06213v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 9 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">2021 ACL Unimplicit Workshop</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.06107">arXiv:2411.06107</a> <span> [<a href="https://arxiv.org/pdf/2411.06107">pdf</a>, <a href="https://arxiv.org/format/2411.06107">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Systems and Control">eess.SY</span> </div> </div> <p class="title is-5 mathjax"> A capacity renting framework for shared energy storage considering peer-to-peer energy trading of prosumers with privacy protection </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Sun%2C+Y">Yingcong Sun</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Laijun Chen</a>, <a href="/search/?searchtype=author&query=Chen%2C+Y">Yue Chen</a>, <a href="/search/?searchtype=author&query=Tang%2C+M">Mingrui Tang</a>, <a href="/search/?searchtype=author&query=Mei%2C+S">Shengwei Mei</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.06107v1-abstract-short" style="display: inline;"> Shared energy storage systems (ESS) present a promising solution to the temporal imbalance between energy generation from renewable distributed generators (DGs) and the power demands of prosumers. However, as DG penetration rates rise, spatial energy imbalances become increasingly significant, necessitating the integration of peer-to-peer (P2P) energy trading within the shared ESS framework. Two k… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.06107v1-abstract-full').style.display = 'inline'; document.getElementById('2411.06107v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.06107v1-abstract-full" style="display: none;"> Shared energy storage systems (ESS) present a promising solution to the temporal imbalance between energy generation from renewable distributed generators (DGs) and the power demands of prosumers. However, as DG penetration rates rise, spatial energy imbalances become increasingly significant, necessitating the integration of peer-to-peer (P2P) energy trading within the shared ESS framework. Two key challenges emerge in this context: the absence of effective mechanisms and the greater difficulty for privacy protection due to increased data communication. This research proposes a capacity renting framework for shared ESS considering P2P energy trading of prosumers. In the proposed framework, prosumers can participate in P2P energy trading and rent capacities from shared ESS. A generalized Nash game is formulated to model the trading process and the competitive interactions among prosumers, and the variational equilibrium of the game is proved to be equivalent to the optimal solution of a quadratic programming (QP) problem. To address the privacy protection concern, the problem is solved using the alternating direction method of multipliers (ADMM) with the Paillier cryptosystem. Finally, numerical simulations demonstrate the impact of P2P energy trading on the shared ESS framework and validate the effectiveness of the proposed privacy-preserving algorithm. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.06107v1-abstract-full').style.display = 'none'; document.getElementById('2411.06107v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 9 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.05959">arXiv:2411.05959</a> <span> [<a href="https://arxiv.org/pdf/2411.05959">pdf</a>, <a href="https://arxiv.org/format/2411.05959">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Image and Video Processing">eess.IV</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> </div> </div> <p class="title is-5 mathjax"> Efficient Self-Supervised Barlow Twins from Limited Tissue Slide Cohorts for Colonic Pathology Diagnostics </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Notton%2C+C">Cassandre Notton</a>, <a href="/search/?searchtype=author&query=Sharma%2C+V">Vasudev Sharma</a>, <a href="/search/?searchtype=author&query=Trinh%2C+V+Q">Vincent Quoc-Huy Trinh</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Lina Chen</a>, <a href="/search/?searchtype=author&query=Xu%2C+M">Minqi Xu</a>, <a href="/search/?searchtype=author&query=Varma%2C+S">Sonal Varma</a>, <a href="/search/?searchtype=author&query=Hosseini%2C+M+S">Mahdi S. Hosseini</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.05959v1-abstract-short" style="display: inline;"> Colorectal cancer (CRC) is one of the few cancers that have an established dysplasia-carcinoma sequence that benefits from screening. Everyone over 50 years of age in Canada is eligible for CRC screening. About 20\% of those people will undergo a biopsy for a pre-neoplastic polyp and, in many cases, multiple polyps. As such, these polyp biopsies make up the bulk of a pathologist's workload. Develo… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.05959v1-abstract-full').style.display = 'inline'; document.getElementById('2411.05959v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.05959v1-abstract-full" style="display: none;"> Colorectal cancer (CRC) is one of the few cancers that have an established dysplasia-carcinoma sequence that benefits from screening. Everyone over 50 years of age in Canada is eligible for CRC screening. About 20\% of those people will undergo a biopsy for a pre-neoplastic polyp and, in many cases, multiple polyps. As such, these polyp biopsies make up the bulk of a pathologist's workload. Developing an efficient computational model to help screen these polyp biopsies can improve the pathologist's workflow and help guide their attention to critical areas on the slide. DL models face significant challenges in computational pathology (CPath) because of the gigapixel image size of whole-slide images and the scarcity of detailed annotated datasets. It is, therefore, crucial to leverage self-supervised learning (SSL) methods to alleviate the burden and cost of data annotation. However, current research lacks methods to apply SSL frameworks to analyze pathology data effectively. This paper aims to propose an optimized Barlow Twins framework for colorectal polyps screening. We adapt its hyperparameters, augmentation strategy and encoder to the specificity of the pathology data to enhance performance. Additionally, we investigate the best Field of View (FoV) for colorectal polyps screening and propose a new benchmark dataset for CRC screening, made of four types of colorectal polyps and normal tissue, by performing downstream tasking on MHIST and NCT-CRC-7K datasets. Furthermore, we show that the SSL representations are more meaningful and qualitative than the supervised ones and that Barlow Twins benefits from the Swin Transformer when applied to pathology data. Codes are avaialble from https://github.com/AtlasAnalyticsLab/PathBT. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.05959v1-abstract-full').style.display = 'none'; document.getElementById('2411.05959v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 8 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Submission Under Review</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.05928">arXiv:2411.05928</a> <span> [<a href="https://arxiv.org/pdf/2411.05928">pdf</a>, <a href="https://arxiv.org/format/2411.05928">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> </div> </div> <p class="title is-5 mathjax"> Reducing Distraction in Long-Context Language Models by Focused Learning </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Wu%2C+Z">Zijun Wu</a>, <a href="/search/?searchtype=author&query=Liu%2C+B">Bingyuan Liu</a>, <a href="/search/?searchtype=author&query=Yan%2C+R">Ran Yan</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Lei Chen</a>, <a href="/search/?searchtype=author&query=Delteil%2C+T">Thomas Delteil</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.05928v1-abstract-short" style="display: inline;"> Recent advancements in Large Language Models (LLMs) have significantly enhanced their capacity to process long contexts. However, effectively utilizing this long context remains a challenge due to the issue of distraction, where irrelevant information dominates lengthy contexts, causing LLMs to lose focus on the most relevant segments. To address this, we propose a novel training method that enhan… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.05928v1-abstract-full').style.display = 'inline'; document.getElementById('2411.05928v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.05928v1-abstract-full" style="display: none;"> Recent advancements in Large Language Models (LLMs) have significantly enhanced their capacity to process long contexts. However, effectively utilizing this long context remains a challenge due to the issue of distraction, where irrelevant information dominates lengthy contexts, causing LLMs to lose focus on the most relevant segments. To address this, we propose a novel training method that enhances LLMs' ability to discern relevant information through a unique combination of retrieval-based data augmentation and contrastive learning. Specifically, during fine-tuning with long contexts, we employ a retriever to extract the most relevant segments, serving as augmented inputs. We then introduce an auxiliary contrastive learning objective to explicitly ensure that outputs from the original context and the retrieved sub-context are closely aligned. Extensive experiments on long single-document and multi-document QA benchmarks demonstrate the effectiveness of our proposed method. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.05928v1-abstract-full').style.display = 'none'; document.getElementById('2411.05928v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 8 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.05501">arXiv:2411.05501</a> <span> [<a href="https://arxiv.org/pdf/2411.05501">pdf</a>, <a href="https://arxiv.org/format/2411.05501">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Quantum Physics">quant-ph</span> </div> </div> <p class="title is-5 mathjax"> Multifunctional metalens for trapping and characterizing single atoms </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Chen%2C+G">Guang-Jie Chen</a>, <a href="/search/?searchtype=author&query=Zhao%2C+D">Dong Zhao</a>, <a href="/search/?searchtype=author&query=Wang%2C+Z">Zhu-Bo Wang</a>, <a href="/search/?searchtype=author&query=Li%2C+Z">Ziqin Li</a>, <a href="/search/?searchtype=author&query=Zhang%2C+J">Ji-Zhe Zhang</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Liang Chen</a>, <a href="/search/?searchtype=author&query=Zhang%2C+Y">Yan-Lei Zhang</a>, <a href="/search/?searchtype=author&query=Xu%2C+X">Xin-Biao Xu</a>, <a href="/search/?searchtype=author&query=Liu%2C+A">Ai-Ping Liu</a>, <a href="/search/?searchtype=author&query=Dong%2C+C">Chun-Hua Dong</a>, <a href="/search/?searchtype=author&query=Guo%2C+G">Guang-Can Guo</a>, <a href="/search/?searchtype=author&query=Huang%2C+K">Kun Huang</a>, <a href="/search/?searchtype=author&query=Zou%2C+C">Chang-Ling Zou</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.05501v1-abstract-short" style="display: inline;"> Precise control and manipulation of neutral atoms are essential for quantum technologies but largely dependent on conventional bulky optical setups. Here, we demonstrate a multifunctional metalens that integrates an achromatic lens with large numerical aperture, a quarter-wave plate, and a polarizer for trapping and characterizing single Rubidium atoms. The metalens simultaneously focuses a trappi… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.05501v1-abstract-full').style.display = 'inline'; document.getElementById('2411.05501v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.05501v1-abstract-full" style="display: none;"> Precise control and manipulation of neutral atoms are essential for quantum technologies but largely dependent on conventional bulky optical setups. Here, we demonstrate a multifunctional metalens that integrates an achromatic lens with large numerical aperture, a quarter-wave plate, and a polarizer for trapping and characterizing single Rubidium atoms. The metalens simultaneously focuses a trapping beam at 852\,nm and collects single-photon fluorescence at 780\,nm. We observe a strong dependence of the trapping lifetime on an external bias magnetic field, suggests a complex interplay between the circularly polarized trapping light and the atom's internal states. Our work showcases the potential of metasurfaces in realizing compact and integrated quantum systems based on cold atoms, opening up new possibilities for studying quantum control and manipulation at the nanoscale. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.05501v1-abstract-full').style.display = 'none'; document.getElementById('2411.05501v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 8 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">10 pages, 5 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.05364">arXiv:2411.05364</a> <span> [<a href="https://arxiv.org/pdf/2411.05364">pdf</a>, <a href="https://arxiv.org/format/2411.05364">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Quantum Physics">quant-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Statistical Mechanics">cond-mat.stat-mech</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Strongly Correlated Electrons">cond-mat.str-el</span> </div> </div> <p class="title is-5 mathjax"> Strong-to-weak Symmetry Breaking and Entanglement Transitions </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Chen%2C+L">Langxuan Chen</a>, <a href="/search/?searchtype=author&query=Sun%2C+N">Ning Sun</a>, <a href="/search/?searchtype=author&query=Zhang%2C+P">Pengfei Zhang</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.05364v1-abstract-short" style="display: inline;"> When interacting with an environment, the entanglement within quantum many-body systems is rapidly transferred to the entanglement between the system and the bath. For systems with a large local Hilbert space dimension, this leads to a first-order entanglement transition for the reduced density matrix of the system. On the other hand, recent studies have introduced a new paradigm for classifying d… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.05364v1-abstract-full').style.display = 'inline'; document.getElementById('2411.05364v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.05364v1-abstract-full" style="display: none;"> When interacting with an environment, the entanglement within quantum many-body systems is rapidly transferred to the entanglement between the system and the bath. For systems with a large local Hilbert space dimension, this leads to a first-order entanglement transition for the reduced density matrix of the system. On the other hand, recent studies have introduced a new paradigm for classifying density matrices, with particular focus on scenarios where a strongly symmetric density matrix undergoes spontaneous symmetry breaking to a weak symmetry phase. This is typically characterized by a finite R茅nyi-2 correlator or a finite Wightman correlator. In this work, we study the entanglement transition from the perspective of strong-to-weak symmetry breaking, using solvable complex Brownian SYK models. We perform analytical calculations for both the early-time and late-time saddles. The results show that while the R茅nyi-2 correlator indicates a transition from symmetric to symmetry-broken phase, the Wightman correlator becomes finite even in the early-time saddle due to the single-replica limit, demonstrating that the first-order transition occurs between a near-symmetric phase and a deeply symmetry-broken phase in the sense of Wightman correlator. Our results provide a novel viewpoint on the entanglement transition under symmetry constraints and can be readily generalized to systems with repeated measurements. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.05364v1-abstract-full').style.display = 'none'; document.getElementById('2411.05364v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 8 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">7 pages, 1 figure</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.04978">arXiv:2411.04978</a> <span> [<a href="https://arxiv.org/pdf/2411.04978">pdf</a>, <a href="https://arxiv.org/format/2411.04978">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="High Energy Physics - Theory">hep-th</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Quantum Physics">quant-ph</span> </div> </div> <p class="title is-5 mathjax"> Holographic pseudoentanglement and the complexity of the AdS/CFT dictionary </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Akers%2C+C">Chris Akers</a>, <a href="/search/?searchtype=author&query=Bouland%2C+A">Adam Bouland</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Lijie Chen</a>, <a href="/search/?searchtype=author&query=Kohler%2C+T">Tamara Kohler</a>, <a href="/search/?searchtype=author&query=Metger%2C+T">Tony Metger</a>, <a href="/search/?searchtype=author&query=Vazirani%2C+U">Umesh Vazirani</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.04978v1-abstract-short" style="display: inline;"> The `quantum gravity in the lab' paradigm suggests that quantum computers might shed light on quantum gravity by simulating the CFT side of the AdS/CFT correspondence and mapping the results to the AdS side. This relies on the assumption that the duality map (the `dictionary') is efficient to compute. In this work, we show that the complexity of the AdS/CFT dictionary is surprisingly subtle: there… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.04978v1-abstract-full').style.display = 'inline'; document.getElementById('2411.04978v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.04978v1-abstract-full" style="display: none;"> The `quantum gravity in the lab' paradigm suggests that quantum computers might shed light on quantum gravity by simulating the CFT side of the AdS/CFT correspondence and mapping the results to the AdS side. This relies on the assumption that the duality map (the `dictionary') is efficient to compute. In this work, we show that the complexity of the AdS/CFT dictionary is surprisingly subtle: there might be cases in which one can efficiently apply operators to the CFT state (a task we call 'operator reconstruction') without being able to extract basic properties of the dual bulk state such as its geometry (which we call 'geometry reconstruction'). Geometry reconstruction corresponds to the setting where we want to extract properties of a completely unknown bulk dual from a simulated CFT boundary state. We demonstrate that geometry reconstruction may be generically hard due to the connection between geometry and entanglement in holography. In particular we construct ensembles of states whose entanglement approximately obey the Ryu-Takayanagi formula for arbitrary geometries, but which are nevertheless computationally indistinguishable. This suggests that even for states with the special entanglement structure of holographic CFT states, geometry reconstruction might be hard. This result should be compared with existing evidence that operator reconstruction is generically easy in AdS/CFT. A useful analogy for the difference between these two tasks is quantum fully homomorphic encryption (FHE): this encrypts quantum states in such a way that no efficient adversary can learn properties of the state, but operators can be applied efficiently to the encrypted state. We show that quantum FHE can separate the complexity of geometry reconstruction vs operator reconstruction, which raises the question whether FHE could be a useful lens through which to view AdS/CFT. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.04978v1-abstract-full').style.display = 'none'; document.getElementById('2411.04978v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 7 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">45 pages, 9 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.04442">arXiv:2411.04442</a> <span> [<a href="https://arxiv.org/pdf/2411.04442">pdf</a>, <a href="https://arxiv.org/format/2411.04442">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Quantum Physics">quant-ph</span> </div> </div> <p class="title is-5 mathjax"> Benchmarking Single-Qubit Gates on a Noise-Biased Qubit Beyond the Fault-Tolerant Threshold </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Qing%2C+B">Bingcheng Qing</a>, <a href="/search/?searchtype=author&query=Hajr%2C+A">Ahmed Hajr</a>, <a href="/search/?searchtype=author&query=Wang%2C+K">Ke Wang</a>, <a href="/search/?searchtype=author&query=Koolstra%2C+G">Gerwin Koolstra</a>, <a href="/search/?searchtype=author&query=Nguyen%2C+L+B">Long B. Nguyen</a>, <a href="/search/?searchtype=author&query=Hines%2C+J">Jordan Hines</a>, <a href="/search/?searchtype=author&query=Huang%2C+I">Irwin Huang</a>, <a href="/search/?searchtype=author&query=Bhandari%2C+B">Bibek Bhandari</a>, <a href="/search/?searchtype=author&query=Padramrazi%2C+Z">Zahra Padramrazi</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Larry Chen</a>, <a href="/search/?searchtype=author&query=Kang%2C+Z">Ziqi Kang</a>, <a href="/search/?searchtype=author&query=J%C3%BCnger%2C+C">Christian J眉nger</a>, <a href="/search/?searchtype=author&query=Goss%2C+N">Noah Goss</a>, <a href="/search/?searchtype=author&query=Jain%2C+N">Nikitha Jain</a>, <a href="/search/?searchtype=author&query=Kim%2C+H">Hyunseong Kim</a>, <a href="/search/?searchtype=author&query=Lee%2C+K">Kan-Heng Lee</a>, <a href="/search/?searchtype=author&query=Hashim%2C+A">Akel Hashim</a>, <a href="/search/?searchtype=author&query=Frattini%2C+N+E">Nicholas E. Frattini</a>, <a href="/search/?searchtype=author&query=Dressel%2C+J">Justin Dressel</a>, <a href="/search/?searchtype=author&query=Jordan%2C+A+N">Andrew N. Jordan</a>, <a href="/search/?searchtype=author&query=Santiago%2C+D+I">David I. Santiago</a>, <a href="/search/?searchtype=author&query=Siddiqi%2C+I">Irfan Siddiqi</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.04442v1-abstract-short" style="display: inline;"> The ubiquitous noise in quantum system hinders the advancement of quantum information processing and has driven the emergence of different hardware-efficient quantum error correction protocols. Among them, qubits with structured noise, especially with biased noise, are one of the most promising platform to achieve fault-tolerance due to the high error thresholds of quantum error correction codes t… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.04442v1-abstract-full').style.display = 'inline'; document.getElementById('2411.04442v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.04442v1-abstract-full" style="display: none;"> The ubiquitous noise in quantum system hinders the advancement of quantum information processing and has driven the emergence of different hardware-efficient quantum error correction protocols. Among them, qubits with structured noise, especially with biased noise, are one of the most promising platform to achieve fault-tolerance due to the high error thresholds of quantum error correction codes tailored for them. Nevertheless, their quantum operations are challenging and the demonstration of their performance beyond the fault-tolerant threshold remain incomplete. Here, we leverage Schr枚dinger cat states in a scalable planar superconducting nonlinear oscillator to thoroughly characterize the high-fidelity single-qubit quantum operations with systematic quantum tomography and benchmarking tools, demonstrating the state-of-the-art performance of operations crossing the fault-tolerant threshold of the XZZX surface code. These results thus embody a transformative milestone in the exploration of quantum systems with structured error channels. Notably, our framework is extensible to other types of structured-noise systems, paving the way for systematic characterization and validation of novel quantum platforms with structured noise. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.04442v1-abstract-full').style.display = 'none'; document.getElementById('2411.04442v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 7 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">19 pages, 12 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.03787">arXiv:2411.03787</a> <span> [<a href="https://arxiv.org/pdf/2411.03787">pdf</a>, <a href="https://arxiv.org/format/2411.03787">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Astrophysics of Galaxies">astro-ph.GA</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Solar and Stellar Astrophysics">astro-ph.SR</span> </div> </div> <p class="title is-5 mathjax"> Unveiling the Binary Nature of NGC 2323 </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Qin%2C+S">Songmei Qin</a>, <a href="/search/?searchtype=author&query=Zhong%2C+J">Jing Zhong</a>, <a href="/search/?searchtype=author&query=Tang%2C+T">Tong Tang</a>, <a href="/search/?searchtype=author&query=Jiang%2C+Y">Yueyue Jiang</a>, <a href="/search/?searchtype=author&query=Wang%2C+L">Long Wang</a>, <a href="/search/?searchtype=author&query=Wu%2C+K">Kai Wu</a>, <a href="/search/?searchtype=author&query=Anders%2C+F">Friedrich Anders</a>, <a href="/search/?searchtype=author&query=Balaguer-N%C3%BA%C3%B1ez%2C+L">Lola Balaguer-N煤帽ez</a>, <a href="/search/?searchtype=author&query=Liu%2C+G">Guimei Liu</a>, <a href="/search/?searchtype=author&query=Li%2C+C">Chunyan Li</a>, <a href="/search/?searchtype=author&query=Hou%2C+J">Jinliang Hou</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Li Chen</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.03787v1-abstract-short" style="display: inline;"> As a well-known open cluster, NGC 2323 (also called M50) has been widely investigated for over a hundred years and has always been considered a classical single cluster. In this work, with the help of Gaia DR3, we study the binary structure nature of this cluster. Although indistinguishable in the spatial space, the small but undeniable difference in the proper motion indicates that they may be tw… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.03787v1-abstract-full').style.display = 'inline'; document.getElementById('2411.03787v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.03787v1-abstract-full" style="display: none;"> As a well-known open cluster, NGC 2323 (also called M50) has been widely investigated for over a hundred years and has always been considered a classical single cluster. In this work, with the help of Gaia DR3, we study the binary structure nature of this cluster. Although indistinguishable in the spatial space, the small but undeniable difference in the proper motion indicates that they may be two individual clusters. After investigating the properties of the two clusters, it is found that they have very close positions (three-dimensional $螖$pos = 12.3 pc, $蟽_{螖\mathrm{pos}} = 3.4$ pc) and similar tangential velocities (two-dimensional $螖$V = 2.2 km s$^{-1}$, $蟽_{螖\mathrm{V}} = 0.02$ km s$^{-1}$), indicating the existence of their physical association. Moreover, the best isochrone fitting ages of the two clusters are the same (158 Myr), further proving their possibly common origin. To comprehensively understand the formation and evolution of this binary cluster, we employ the PETAR $N$-body code to trace back their birthplace and deduce their dynamical evolutionary fate. With observational mean cluster properties, the simulations suggest that they may form together, and then orbit each other as a binary cluster for over 200 Myr. After that, because of their gradual mass loss, the two clusters will eventually separate and evolve into two independent clusters. Meanwhile, the numerical $N$-body simulation suggests that the less massive cluster is unlikely to be the cluster tidal tails created by the differential rotation of the Milky Way. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.03787v1-abstract-full').style.display = 'none'; document.getElementById('2411.03787v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 6 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">14 pages, 8 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.03707">arXiv:2411.03707</a> <span> [<a href="https://arxiv.org/pdf/2411.03707">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> </div> </div> <p class="title is-5 mathjax"> Fine-Tuning Vision-Language Model for Automated Engineering Drawing Information Extraction </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Khan%2C+M+T">Muhammad Tayyab Khan</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Lequn Chen</a>, <a href="/search/?searchtype=author&query=Ng%2C+Y+H">Ye Han Ng</a>, <a href="/search/?searchtype=author&query=Feng%2C+W">Wenhe Feng</a>, <a href="/search/?searchtype=author&query=Tan%2C+N+Y+J">Nicholas Yew Jin Tan</a>, <a href="/search/?searchtype=author&query=Moon%2C+S+K">Seung Ki Moon</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.03707v1-abstract-short" style="display: inline;"> Geometric Dimensioning and Tolerancing (GD&T) plays a critical role in manufacturing by defining acceptable variations in part features to ensure component quality and functionality. However, extracting GD&T information from 2D engineering drawings is a time-consuming and labor-intensive task, often relying on manual efforts or semi-automated tools. To address these challenges, this study proposes… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.03707v1-abstract-full').style.display = 'inline'; document.getElementById('2411.03707v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.03707v1-abstract-full" style="display: none;"> Geometric Dimensioning and Tolerancing (GD&T) plays a critical role in manufacturing by defining acceptable variations in part features to ensure component quality and functionality. However, extracting GD&T information from 2D engineering drawings is a time-consuming and labor-intensive task, often relying on manual efforts or semi-automated tools. To address these challenges, this study proposes an automated and computationally efficient GD&T extraction method by fine-tuning Florence-2, an open-source vision-language model (VLM). The model is trained on a dataset of 400 drawings with ground truth annotations provided by domain experts. For comparison, two state-of-the-art closed-source VLMs, GPT-4o and Claude-3.5-Sonnet, are evaluated on the same dataset. All models are assessed using precision, recall, F1-score, and hallucination metrics. Due to the computational cost and impracticality of fine-tuning large closed-source VLMs for domain-specific tasks, GPT-4o and Claude-3.5-Sonnet are evaluated in a zero-shot setting. In contrast, Florence-2, a smaller model with 0.23 billion parameters, is optimized through full-parameter fine-tuning across three distinct experiments, each utilizing datasets augmented to different levels. The results show that Florence-2 achieves a 29.95% increase in precision, a 37.75% increase in recall, a 52.40% improvement in F1-score, and a 43.15% reduction in hallucination rate compared to the best-performing closed-source model. These findings highlight the effectiveness of fine-tuning smaller, open-source VLMs like Florence-2, offering a practical and efficient solution for automated GD&T extraction to support downstream manufacturing tasks. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.03707v1-abstract-full').style.display = 'none'; document.getElementById('2411.03707v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 6 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Paper has been submitted to the 9th International Conference on Innovation in Artificial Intelligence (ICIAI 2025)</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.03389">arXiv:2411.03389</a> <span> [<a href="https://arxiv.org/pdf/2411.03389">pdf</a>, <a href="https://arxiv.org/format/2411.03389">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computational Physics">physics.comp-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> </div> </div> <p class="title is-5 mathjax"> Neurons for Neutrons: A Transformer Model for Computation Load Estimation on Domain-Decomposed Neutron Transport Problems </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Mote%2C+A">Alexander Mote</a>, <a href="/search/?searchtype=author&query=Palmer%2C+T">Todd Palmer</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Lizhong Chen</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.03389v2-abstract-short" style="display: inline;"> Domain decomposition is a technique used to reduce memory overhead on large neutron transport problems. Currently, the optimal load-balanced processor allocation for these domains is typically determined through small-scale simulations of the problem, which can be time-consuming for researchers and must be repeated anytime a problem input is changed. We propose a Transformer model with a unique 3D… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.03389v2-abstract-full').style.display = 'inline'; document.getElementById('2411.03389v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.03389v2-abstract-full" style="display: none;"> Domain decomposition is a technique used to reduce memory overhead on large neutron transport problems. Currently, the optimal load-balanced processor allocation for these domains is typically determined through small-scale simulations of the problem, which can be time-consuming for researchers and must be repeated anytime a problem input is changed. We propose a Transformer model with a unique 3D input embedding, and input representations designed for domain-decomposed neutron transport problems, which can predict the subdomain computation loads generated by small-scale simulations. We demonstrate that such a model trained on domain-decomposed Small Modular Reactor (SMR) simulations achieves 98.2% accuracy while being able to skip the small-scale simulation step entirely. Tests of the model's robustness on variant fuel assemblies, other problem geometries, and changes in simulation parameters are also discussed. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.03389v2-abstract-full').style.display = 'none'; document.getElementById('2411.03389v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 7 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 5 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">28 pages, 14 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.02886">arXiv:2411.02886</a> <span> [<a href="https://arxiv.org/pdf/2411.02886">pdf</a>, <a href="https://arxiv.org/format/2411.02886">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> </div> <p class="title is-5 mathjax"> TokenSelect: Efficient Long-Context Inference and Length Extrapolation for LLMs via Dynamic Token-Level KV Cache Selection </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Wu%2C+W">Wei Wu</a>, <a href="/search/?searchtype=author&query=Pan%2C+Z">Zhuoshi Pan</a>, <a href="/search/?searchtype=author&query=Wang%2C+C">Chao Wang</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Liyi Chen</a>, <a href="/search/?searchtype=author&query=Bai%2C+Y">Yunchu Bai</a>, <a href="/search/?searchtype=author&query=Fu%2C+K">Kun Fu</a>, <a href="/search/?searchtype=author&query=Wang%2C+Z">Zheng Wang</a>, <a href="/search/?searchtype=author&query=Xiong%2C+H">Hui Xiong</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.02886v1-abstract-short" style="display: inline;"> With the development of large language models (LLMs), the ability to handle longer contexts has become a key capability for Web applications such as cross-document understanding and LLM-powered search systems. However, this progress faces two major challenges: performance degradation due to sequence lengths out-of-distribution, and excessively long inference times caused by the quadratic computati… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.02886v1-abstract-full').style.display = 'inline'; document.getElementById('2411.02886v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.02886v1-abstract-full" style="display: none;"> With the development of large language models (LLMs), the ability to handle longer contexts has become a key capability for Web applications such as cross-document understanding and LLM-powered search systems. However, this progress faces two major challenges: performance degradation due to sequence lengths out-of-distribution, and excessively long inference times caused by the quadratic computational complexity of attention. These issues hinder the application of LLMs in long-context scenarios. In this paper, we propose Dynamic Token-Level KV Cache Selection (TokenSelect), a model-agnostic, training-free method for efficient and accurate long-context inference. TokenSelect builds upon the observation of non-contiguous attention sparsity, using Query-Key dot products to measure per-head KV Cache criticality at token-level. By per-head soft voting mechanism, TokenSelect selectively involves a small number of critical KV cache tokens in the attention calculation without sacrificing accuracy. To further accelerate TokenSelect, we designed the Selection Cache based on observations of consecutive Query similarity and implemented efficient dot product kernel, significantly reducing the overhead of token selection. A comprehensive evaluation of TokenSelect demonstrates up to 23.84x speedup in attention computation and up to 2.28x acceleration in end-to-end latency, while providing superior performance compared to state-of-the-art long-context inference methods. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.02886v1-abstract-full').style.display = 'none'; document.getElementById('2411.02886v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 5 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.02810">arXiv:2411.02810</a> <span> [<a href="https://arxiv.org/pdf/2411.02810">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computational Engineering, Finance, and Science">cs.CE</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Information Retrieval">cs.IR</span> </div> </div> <p class="title is-5 mathjax"> Leveraging Vision-Language Models for Manufacturing Feature Recognition in CAD Designs </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Khan%2C+M+T">Muhammad Tayyab Khan</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Lequn Chen</a>, <a href="/search/?searchtype=author&query=Ng%2C+Y+H">Ye Han Ng</a>, <a href="/search/?searchtype=author&query=Feng%2C+W">Wenhe Feng</a>, <a href="/search/?searchtype=author&query=Tan%2C+N+Y+J">Nicholas Yew Jin Tan</a>, <a href="/search/?searchtype=author&query=Moon%2C+S+K">Seung Ki Moon</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.02810v1-abstract-short" style="display: inline;"> Automatic feature recognition (AFR) is essential for transforming design knowledge into actionable manufacturing information. Traditional AFR methods, which rely on predefined geometric rules and large datasets, are often time-consuming and lack generalizability across various manufacturing features. To address these challenges, this study investigates vision-language models (VLMs) for automating… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.02810v1-abstract-full').style.display = 'inline'; document.getElementById('2411.02810v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.02810v1-abstract-full" style="display: none;"> Automatic feature recognition (AFR) is essential for transforming design knowledge into actionable manufacturing information. Traditional AFR methods, which rely on predefined geometric rules and large datasets, are often time-consuming and lack generalizability across various manufacturing features. To address these challenges, this study investigates vision-language models (VLMs) for automating the recognition of a wide range of manufacturing features in CAD designs without the need for extensive training datasets or predefined rules. Instead, prompt engineering techniques, such as multi-view query images, few-shot learning, sequential reasoning, and chain-of-thought, are applied to enable recognition. The approach is evaluated on a newly developed CAD dataset containing designs of varying complexity relevant to machining, additive manufacturing, sheet metal forming, molding, and casting. Five VLMs, including three closed-source models (GPT-4o, Claude-3.5-Sonnet, and Claude-3.0-Opus) and two open-source models (LLava and MiniCPM), are evaluated on this dataset with ground truth features labelled by experts. Key metrics include feature quantity accuracy, feature name matching accuracy, hallucination rate, and mean absolute error (MAE). Results show that Claude-3.5-Sonnet achieves the highest feature quantity accuracy (74%) and name-matching accuracy (75%) with the lowest MAE (3.2), while GPT-4o records the lowest hallucination rate (8%). In contrast, open-source models have higher hallucination rates (>30%) and lower accuracies (<40%). This study demonstrates the potential of VLMs to automate feature recognition in CAD designs within diverse manufacturing scenarios. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.02810v1-abstract-full').style.display = 'none'; document.getElementById('2411.02810v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 4 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Paper has been submitted to The ASME Journal of Computing and Information Science in Engineering (JCISE)</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.02497">arXiv:2411.02497</a> <span> [<a href="https://arxiv.org/pdf/2411.02497">pdf</a>, <a href="https://arxiv.org/format/2411.02497">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="High Energy Astrophysical Phenomena">astro-ph.HE</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Solar and Stellar Astrophysics">astro-ph.SR</span> </div> </div> <p class="title is-5 mathjax"> Asymmetries and Circumstellar Interaction in the Type II SN 2024bch </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Andrews%2C+J+E">Jennifer E. Andrews</a>, <a href="/search/?searchtype=author&query=Shrestha%2C+M">Manisha Shrestha</a>, <a href="/search/?searchtype=author&query=Bostroem%2C+K+A">K. Azalee Bostroem</a>, <a href="/search/?searchtype=author&query=Dong%2C+Y">Yize Dong</a>, <a href="/search/?searchtype=author&query=Pearson%2C+J">Jeniveve Pearson</a>, <a href="/search/?searchtype=author&query=Fausnaugh%2C+M+M">M. M. Fausnaugh</a>, <a href="/search/?searchtype=author&query=Sand%2C+D+J">David J. Sand</a>, <a href="/search/?searchtype=author&query=Valenti%2C+S">S. Valenti</a>, <a href="/search/?searchtype=author&query=Ravi%2C+A+P">Aravind P. Ravi</a>, <a href="/search/?searchtype=author&query=Hoang%2C+E">Emily Hoang</a>, <a href="/search/?searchtype=author&query=Hosseinzadeh%2C+G">Griffin Hosseinzadeh</a>, <a href="/search/?searchtype=author&query=Ilyin%2C+I">Ilya Ilyin</a>, <a href="/search/?searchtype=author&query=Janzen%2C+D">Daryl Janzen</a>, <a href="/search/?searchtype=author&query=Lundquist%2C+M+J">M. J. Lundquist</a>, <a href="/search/?searchtype=author&query=Meza%2C+N">Nicolaz Meza</a>, <a href="/search/?searchtype=author&query=Smith%2C+N">Nathan Smith</a>, <a href="/search/?searchtype=author&query=Jha%2C+S+W">Saurabh W. Jha</a>, <a href="/search/?searchtype=author&query=Andrews%2C+M">Moira Andrews</a>, <a href="/search/?searchtype=author&query=Farah%2C+J">Joseph Farah</a>, <a href="/search/?searchtype=author&query=Gonzalez%2C+E+P">Estefania Padilla Gonzalez</a>, <a href="/search/?searchtype=author&query=Howell%2C+D+A">D. Andrew Howell</a>, <a href="/search/?searchtype=author&query=McCully%2C+C">Curtis McCully</a>, <a href="/search/?searchtype=author&query=Newsome%2C+M">Megan Newsome</a>, <a href="/search/?searchtype=author&query=Pellegrino%2C+C">Craig Pellegrino</a>, <a href="/search/?searchtype=author&query=Terreran%2C+G">Giacomo Terreran</a> , et al. (6 additional authors not shown) </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.02497v1-abstract-short" style="display: inline;"> We present a comprehensive multi-epoch photometric and spectroscopic study of SN 2024bch, a nearby (19.9 Mpc) Type II supernova (SN) with prominent early high ionization emission lines. Optical spectra from 2.9 days after the estimated explosion reveal narrow lines of H I, He II, C IV, and N IV that disappear by day 6. High cadence photometry from the ground and TESS show that the SN brightened qu… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.02497v1-abstract-full').style.display = 'inline'; document.getElementById('2411.02497v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.02497v1-abstract-full" style="display: none;"> We present a comprehensive multi-epoch photometric and spectroscopic study of SN 2024bch, a nearby (19.9 Mpc) Type II supernova (SN) with prominent early high ionization emission lines. Optical spectra from 2.9 days after the estimated explosion reveal narrow lines of H I, He II, C IV, and N IV that disappear by day 6. High cadence photometry from the ground and TESS show that the SN brightened quickly and reached a peak M$_V \sim$ $-$17.8 mag within a week of explosion, and late-time photometry suggests a $^{56}$Ni mass of 0.050 M$_{\odot}$. High-resolution spectra from day 8 and 43 trace the unshocked circumstellar medium (CSM) and indicate a wind velocity of 30--40 km s$^{-1}$, a value consistent with a red supergiant (RSG) progenitor. Comparisons between models and the early spectra suggest a pre-SN mass-loss rate of $\dot{M} \sim 10^{-3}-10^{-2}\ M_\odot\ \mathrm{yr}^{-1}$, which is too high to be explained by quiescent mass loss from RSGs, but is consistent with some recent measurements of similar SNe. Persistent blueshifted H I and [O I] emission lines seen in the optical and NIR spectra could be produced by asymmetries in the SN ejecta, while the multi-component H$伪$ may indicate continued interaction with an asymmetric CSM well into the nebular phase. SN 2024bch provides another clue to the complex environments and mass-loss histories around massive stars. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.02497v1-abstract-full').style.display = 'none'; document.getElementById('2411.02497v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 4 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Submitted to ApJ</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.02041">arXiv:2411.02041</a> <span> [<a href="https://arxiv.org/pdf/2411.02041">pdf</a>, <a href="https://arxiv.org/format/2411.02041">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Retrieval">cs.IR</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> </div> </div> <p class="title is-5 mathjax"> Enhancing ID-based Recommendation with Large Language Models </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Chen%2C+L">Lei Chen</a>, <a href="/search/?searchtype=author&query=Gao%2C+C">Chen Gao</a>, <a href="/search/?searchtype=author&query=Du%2C+X">Xiaoyi Du</a>, <a href="/search/?searchtype=author&query=Luo%2C+H">Hengliang Luo</a>, <a href="/search/?searchtype=author&query=Jin%2C+D">Depeng Jin</a>, <a href="/search/?searchtype=author&query=Li%2C+Y">Yong Li</a>, <a href="/search/?searchtype=author&query=Wang%2C+M">Meng Wang</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.02041v1-abstract-short" style="display: inline;"> Large Language Models (LLMs) have recently garnered significant attention in various domains, including recommendation systems. Recent research leverages the capabilities of LLMs to improve the performance and user modeling aspects of recommender systems. These studies primarily focus on utilizing LLMs to interpret textual data in recommendation tasks. However, it's worth noting that in ID-based r… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.02041v1-abstract-full').style.display = 'inline'; document.getElementById('2411.02041v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.02041v1-abstract-full" style="display: none;"> Large Language Models (LLMs) have recently garnered significant attention in various domains, including recommendation systems. Recent research leverages the capabilities of LLMs to improve the performance and user modeling aspects of recommender systems. These studies primarily focus on utilizing LLMs to interpret textual data in recommendation tasks. However, it's worth noting that in ID-based recommendations, textual data is absent, and only ID data is available. The untapped potential of LLMs for ID data within the ID-based recommendation paradigm remains relatively unexplored. To this end, we introduce a pioneering approach called "LLM for ID-based Recommendation" (LLM4IDRec). This innovative approach integrates the capabilities of LLMs while exclusively relying on ID data, thus diverging from the previous reliance on textual data. The basic idea of LLM4IDRec is that by employing LLM to augment ID data, if augmented ID data can improve recommendation performance, it demonstrates the ability of LLM to interpret ID data effectively, exploring an innovative way for the integration of LLM in ID-based recommendation. We evaluate the effectiveness of our LLM4IDRec approach using three widely-used datasets. Our results demonstrate a notable improvement in recommendation performance, with our approach consistently outperforming existing methods in ID-based recommendation by solely augmenting input data. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.02041v1-abstract-full').style.display = 'none'; document.getElementById('2411.02041v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 4 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.02006">arXiv:2411.02006</a> <span> [<a href="https://arxiv.org/pdf/2411.02006">pdf</a>, <a href="https://arxiv.org/format/2411.02006">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> </div> </div> <p class="title is-5 mathjax"> Foundations and Recent Trends in Multimodal Mobile Agents: A Survey </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Wu%2C+B">Biao Wu</a>, <a href="/search/?searchtype=author&query=Li%2C+Y">Yanda Li</a>, <a href="/search/?searchtype=author&query=Fang%2C+M">Meng Fang</a>, <a href="/search/?searchtype=author&query=Song%2C+Z">Zirui Song</a>, <a href="/search/?searchtype=author&query=Zhang%2C+Z">Zhiwei Zhang</a>, <a href="/search/?searchtype=author&query=Wei%2C+Y">Yunchao Wei</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Ling Chen</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.02006v1-abstract-short" style="display: inline;"> Mobile agents are essential for automating tasks in complex and dynamic mobile environments. As foundation models evolve, the demands for agents that can adapt in real-time and process multimodal data have grown. This survey provides a comprehensive review of mobile agent technologies, focusing on recent advancements that enhance real-time adaptability and multimodal interaction. Recent evaluation… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.02006v1-abstract-full').style.display = 'inline'; document.getElementById('2411.02006v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.02006v1-abstract-full" style="display: none;"> Mobile agents are essential for automating tasks in complex and dynamic mobile environments. As foundation models evolve, the demands for agents that can adapt in real-time and process multimodal data have grown. This survey provides a comprehensive review of mobile agent technologies, focusing on recent advancements that enhance real-time adaptability and multimodal interaction. Recent evaluation benchmarks have been developed better to capture the static and interactive environments of mobile tasks, offering more accurate assessments of agents' performance. We then categorize these advancements into two main approaches: prompt-based methods, which utilize large language models (LLMs) for instruction-based task execution, and training-based methods, which fine-tune multimodal models for mobile-specific applications. Additionally, we explore complementary technologies that augment agent performance. By discussing key challenges and outlining future research directions, this survey offers valuable insights for advancing mobile agent technologies. A comprehensive resource list is available at https://github.com/aialt/awesome-mobile-agents <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.02006v1-abstract-full').style.display = 'none'; document.getElementById('2411.02006v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 4 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">8 pages, 1 figure</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.01988">arXiv:2411.01988</a> <span> [<a href="https://arxiv.org/pdf/2411.01988">pdf</a>, <a href="https://arxiv.org/format/2411.01988">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> </div> </div> <p class="title is-5 mathjax"> QCS:Feature Refining from Quadruplet Cross Similarity for Facial Expression Recognition </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Wang%2C+C">Chengpeng Wang</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Li Chen</a>, <a href="/search/?searchtype=author&query=Wang%2C+L">Lili Wang</a>, <a href="/search/?searchtype=author&query=Li%2C+Z">Zhaofan Li</a>, <a href="/search/?searchtype=author&query=Lv%2C+X">Xuebin Lv</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.01988v1-abstract-short" style="display: inline;"> On facial expression datasets with complex and numerous feature types, where the significance and dominance of labeled features are difficult to predict, facial expression recognition(FER) encounters the challenges of inter-class similarity and intra-class variances, making it difficult to mine effective features. We aim to solely leverage the feature similarity among facial samples to address thi… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.01988v1-abstract-full').style.display = 'inline'; document.getElementById('2411.01988v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.01988v1-abstract-full" style="display: none;"> On facial expression datasets with complex and numerous feature types, where the significance and dominance of labeled features are difficult to predict, facial expression recognition(FER) encounters the challenges of inter-class similarity and intra-class variances, making it difficult to mine effective features. We aim to solely leverage the feature similarity among facial samples to address this. We introduce the Cross Similarity Attention (CSA), an input-output position-sensitive attention mechanism that harnesses feature similarity across different images to compute the corresponding global spatial attention. Based on this, we propose a four-branch circular framework, called Quadruplet Cross Similarity (QCS), to extract discriminative features from the same class and eliminate redundant ones from different classes synchronously to refine cleaner features. The symmetry of the network ensures balanced and stable training and reduces the amount of CSA interaction matrix. Contrastive residual distillation is utilized to transfer the information learned in the cross module back to the base network. The cross-attention module exists during training, and only one base branch is retained during inference. our proposed QCS model outperforms state-of-the-art methods on several popular FER datasets, without requiring additional landmark information or other extra training data. The code is available at https://github.com/birdwcp/QCS. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.01988v1-abstract-full').style.display = 'none'; document.getElementById('2411.01988v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 4 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.01267">arXiv:2411.01267</a> <span> [<a href="https://arxiv.org/pdf/2411.01267">pdf</a>, <a href="https://arxiv.org/format/2411.01267">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">stat.ML</span> </div> </div> <p class="title is-5 mathjax"> ProGen: Revisiting Probabilistic Spatial-Temporal Time Series Forecasting from a Continuous Generative Perspective Using Stochastic Differential Equations </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Gong%2C+M">Mingze Gong</a>, <a href="/search/?searchtype=author&query=Chen%2C+L">Lei Chen</a>, <a href="/search/?searchtype=author&query=Li%2C+J">Jia Li</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.01267v1-abstract-short" style="display: inline;"> Accurate forecasting of spatiotemporal data remains challenging due to complex spatial dependencies and temporal dynamics. The inherent uncertainty and variability in such data often render deterministic models insufficient, prompting a shift towards probabilistic approaches, where diffusion-based generative models have emerged as effective solutions. In this paper, we present ProGen, a novel fram… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.01267v1-abstract-full').style.display = 'inline'; document.getElementById('2411.01267v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.01267v1-abstract-full" style="display: none;"> Accurate forecasting of spatiotemporal data remains challenging due to complex spatial dependencies and temporal dynamics. The inherent uncertainty and variability in such data often render deterministic models insufficient, prompting a shift towards probabilistic approaches, where diffusion-based generative models have emerged as effective solutions. In this paper, we present ProGen, a novel framework for probabilistic spatiotemporal time series forecasting that leverages Stochastic Differential Equations (SDEs) and diffusion-based generative modeling techniques in the continuous domain. By integrating a novel denoising score model, graph neural networks, and a tailored SDE, ProGen provides a robust solution that effectively captures spatiotemporal dependencies while managing uncertainty. Our extensive experiments on four benchmark traffic datasets demonstrate that ProGen outperforms state-of-the-art deterministic and probabilistic models. This work contributes a continuous, diffusion-based generative approach to spatiotemporal forecasting, paving the way for future research in probabilistic modeling and stochastic processes. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.01267v1-abstract-full').style.display = 'none'; document.getElementById('2411.01267v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 2 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> </ol> <nav class="pagination is-small is-centered breathe-horizontal" role="navigation" aria-label="pagination"> <a href="" class="pagination-previous is-invisible">Previous </a> <a href="/search/?searchtype=author&query=Chen%2C+L&start=50" class="pagination-next" >Next </a> <ul class="pagination-list"> <li> <a 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