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class="list-title is-inline-block"><a href="https://arxiv.org/abs/2502.16747">arXiv:2502.16747</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2502.16747">pdf</a>, <a href="https://arxiv.org/format/2502.16747">other</a>]&nbsp;</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> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Software Engineering">cs.SE</span> </div> </div> <p class="title is-5 mathjax"> SQLong: Enhanced NL2SQL for Longer Contexts with LLMs </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Nguyen%2C+D+Q">Dai Quoc Nguyen</a>, <a href="/search/?searchtype=author&amp;query=Hoang%2C+C+D+V">Cong Duy Vu Hoang</a>, <a href="/search/?searchtype=author&amp;query=Vu%2C+D">Duy Vu</a>, <a href="/search/?searchtype=author&amp;query=Tangari%2C+G">Gioacchino Tangari</a>, <a href="/search/?searchtype=author&amp;query=Vu%2C+T+T">Thanh Tien Vu</a>, <a href="/search/?searchtype=author&amp;query=Dharmasiri%2C+D">Don Dharmasiri</a>, <a href="/search/?searchtype=author&amp;query=Li%2C+Y">Yuan-Fang Li</a>, <a href="/search/?searchtype=author&amp;query=Duong%2C+L">Long Duong</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="2502.16747v1-abstract-short" style="display: inline;"> Open-weight large language models (LLMs) have significantly advanced performance in the Natural Language to SQL (NL2SQL) task. However, their effectiveness diminishes when dealing with large database schemas, as the context length increases. To address this limitation, we present SQLong, a novel and efficient data augmentation framework designed to enhance LLM performance in long-context scenarios&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2502.16747v1-abstract-full').style.display = 'inline'; document.getElementById('2502.16747v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2502.16747v1-abstract-full" style="display: none;"> Open-weight large language models (LLMs) have significantly advanced performance in the Natural Language to SQL (NL2SQL) task. However, their effectiveness diminishes when dealing with large database schemas, as the context length increases. To address this limitation, we present SQLong, a novel and efficient data augmentation framework designed to enhance LLM performance in long-context scenarios for the NL2SQL task. SQLong generates augmented datasets by extending existing database schemas with additional synthetic CREATE TABLE commands and corresponding data rows, sampled from diverse schemas in the training data. This approach effectively simulates long-context scenarios during finetuning and evaluation. Through experiments on the Spider and BIRD datasets, we demonstrate that LLMs finetuned with SQLong-augmented data significantly outperform those trained on standard datasets. These imply SQLong&#39;s practical implementation and its impact on improving NL2SQL capabilities in real-world settings with complex database schemas. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2502.16747v1-abstract-full').style.display = 'none'; document.getElementById('2502.16747v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 23 February, 2025; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2025. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2502.08149">arXiv:2502.08149</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2502.08149">pdf</a>, <a href="https://arxiv.org/format/2502.08149">other</a>]&nbsp;</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"> Generalized Class Discovery in Instance Segmentation </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+C+M">Cuong Manh Hoang</a>, <a href="/search/?searchtype=author&amp;query=Lee%2C+Y">Yeejin Lee</a>, <a href="/search/?searchtype=author&amp;query=Kang%2C+B">Byeongkeun Kang</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="2502.08149v1-abstract-short" style="display: inline;"> This work addresses the task of generalized class discovery (GCD) in instance segmentation. The goal is to discover novel classes and obtain a model capable of segmenting instances of both known and novel categories, given labeled and unlabeled data. Since the real world contains numerous objects with long-tailed distributions, the instance distribution for each class is inherently imbalanced. To&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2502.08149v1-abstract-full').style.display = 'inline'; document.getElementById('2502.08149v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2502.08149v1-abstract-full" style="display: none;"> This work addresses the task of generalized class discovery (GCD) in instance segmentation. The goal is to discover novel classes and obtain a model capable of segmenting instances of both known and novel categories, given labeled and unlabeled data. Since the real world contains numerous objects with long-tailed distributions, the instance distribution for each class is inherently imbalanced. To address the imbalanced distributions, we propose an instance-wise temperature assignment (ITA) method for contrastive learning and class-wise reliability criteria for pseudo-labels. The ITA method relaxes instance discrimination for samples belonging to head classes to enhance GCD. The reliability criteria are to avoid excluding most pseudo-labels for tail classes when training an instance segmentation network using pseudo-labels from GCD. Additionally, we propose dynamically adjusting the criteria to leverage diverse samples in the early stages while relying only on reliable pseudo-labels in the later stages. We also introduce an efficient soft attention module to encode object-specific representations for GCD. Finally, we evaluate our proposed method by conducting experiments on two settings: COCO$_{half}$ + LVIS and LVIS + Visual Genome. The experimental results demonstrate that the proposed method outperforms previous state-of-the-art methods. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2502.08149v1-abstract-full').style.display = 'none'; document.getElementById('2502.08149v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 12 February, 2025; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2025. </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">AAAI 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/2411.12525">arXiv:2411.12525</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2411.12525">pdf</a>, <a href="https://arxiv.org/format/2411.12525">other</a>]&nbsp;</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"> Rethinking Top Probability from Multi-view for Distracted Driver Behaviour Localization </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Nguyen%2C+Q+V">Quang Vinh Nguyen</a>, <a href="/search/?searchtype=author&amp;query=Son%2C+V+H+T">Vo Hoang Thanh Son</a>, <a href="/search/?searchtype=author&amp;query=Hoang%2C+C+T+V">Chau Truong Vinh Hoang</a>, <a href="/search/?searchtype=author&amp;query=Nguyen%2C+D+D">Duc Duy Nguyen</a>, <a href="/search/?searchtype=author&amp;query=Minh%2C+N+H+N">Nhat Huy Nguyen Minh</a>, <a href="/search/?searchtype=author&amp;query=Kim%2C+S">Soo-Hyung Kim</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="2411.12525v1-abstract-short" style="display: inline;"> Naturalistic driving action localization task aims to recognize and comprehend human behaviors and actions from video data captured during real-world driving scenarios. Previous studies have shown great action localization performance by applying a recognition model followed by probability-based post-processing. Nevertheless, the probabilities provided by the recognition model frequently contain c&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.12525v1-abstract-full').style.display = 'inline'; document.getElementById('2411.12525v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.12525v1-abstract-full" style="display: none;"> Naturalistic driving action localization task aims to recognize and comprehend human behaviors and actions from video data captured during real-world driving scenarios. Previous studies have shown great action localization performance by applying a recognition model followed by probability-based post-processing. Nevertheless, the probabilities provided by the recognition model frequently contain confused information causing challenge for post-processing. In this work, we adopt an action recognition model based on self-supervise learning to detect distracted activities and give potential action probabilities. Subsequently, a constraint ensemble strategy takes advantages of multi-camera views to provide robust predictions. Finally, we introduce a conditional post-processing operation to locate distracted behaviours and action temporal boundaries precisely. Experimenting on test set A2, our method obtains the sixth position on the public leaderboard of track 3 of the 2024 AI City Challenge. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.12525v1-abstract-full').style.display = 'none'; document.getElementById('2411.12525v1-abstract-short').style.display = 'inline';">&#9651; 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">Computer Vision and Pattern Recognition Workshop 2024</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.00005">arXiv:2411.00005</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2411.00005">pdf</a>, <a href="https://arxiv.org/format/2411.00005">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Software Engineering">cs.SE</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"> Mastering the Craft of Data Synthesis for CodeLLMs </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Chen%2C+M">Meng Chen</a>, <a href="/search/?searchtype=author&amp;query=Arthur%2C+P">Philip Arthur</a>, <a href="/search/?searchtype=author&amp;query=Feng%2C+Q">Qianyu Feng</a>, <a href="/search/?searchtype=author&amp;query=Hoang%2C+C+D+V">Cong Duy Vu Hoang</a>, <a href="/search/?searchtype=author&amp;query=Hong%2C+Y">Yu-Heng Hong</a>, <a href="/search/?searchtype=author&amp;query=Moghaddam%2C+M+K">Mahdi Kazemi Moghaddam</a>, <a href="/search/?searchtype=author&amp;query=Nezami%2C+O">Omid Nezami</a>, <a href="/search/?searchtype=author&amp;query=Nguyen%2C+T">Thien Nguyen</a>, <a href="/search/?searchtype=author&amp;query=Tangari%2C+G">Gioacchino Tangari</a>, <a href="/search/?searchtype=author&amp;query=Vu%2C+D">Duy Vu</a>, <a href="/search/?searchtype=author&amp;query=Vu%2C+T">Thanh Vu</a>, <a href="/search/?searchtype=author&amp;query=Johnson%2C+M">Mark Johnson</a>, <a href="/search/?searchtype=author&amp;query=Kenthapadi%2C+K">Krishnaram Kenthapadi</a>, <a href="/search/?searchtype=author&amp;query=Dharmasiri%2C+D">Don Dharmasiri</a>, <a href="/search/?searchtype=author&amp;query=Duong%2C+L">Long Duong</a>, <a href="/search/?searchtype=author&amp;query=Li%2C+Y">Yuan-Fang 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="2411.00005v3-abstract-short" style="display: inline;"> Large language models (LLMs) have shown impressive performance in \emph{code} understanding and generation, making coding tasks a key focus for researchers due to their practical applications and value as a testbed for LLM evaluation. Data synthesis and filtering techniques have been widely adopted and shown to be highly effective in this context. In this paper, we present a focused survey and tax&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.00005v3-abstract-full').style.display = 'inline'; document.getElementById('2411.00005v3-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.00005v3-abstract-full" style="display: none;"> Large language models (LLMs) have shown impressive performance in \emph{code} understanding and generation, making coding tasks a key focus for researchers due to their practical applications and value as a testbed for LLM evaluation. Data synthesis and filtering techniques have been widely adopted and shown to be highly effective in this context. In this paper, we present a focused survey and taxonomy of these techniques, emphasizing recent advancements. We highlight key challenges, explore future research directions, and offer practical guidance for new researchers entering the field. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.00005v3-abstract-full').style.display = 'none'; document.getElementById('2411.00005v3-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 7 February, 2025; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 16 October, 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">Accepted at NAACL 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/2410.20705">arXiv:2410.20705</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2410.20705">pdf</a>, <a href="https://arxiv.org/format/2410.20705">other</a>]&nbsp;</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"> Optimization and Characterization of Thermoelectric Properties in Selenium-Doped Bismuth Telluride Ultra Thin Films </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Nguyen%2C+K+T">Kien Trung Nguyen</a>, <a href="/search/?searchtype=author&amp;query=Dong%2C+L+A">Lan Anh Dong</a>, <a href="/search/?searchtype=author&amp;query=Dinh%2C+H+T">Hien Thi Dinh</a>, <a href="/search/?searchtype=author&amp;query=Bui%2C+T+H+T">Thi Huyen Trang Bui</a>, <a href="/search/?searchtype=author&amp;query=Chu%2C+S+T">Son Truong Chu</a>, <a href="/search/?searchtype=author&amp;query=Nguyen-Tran%2C+T">Thuat Nguyen-Tran</a>, <a href="/search/?searchtype=author&amp;query=Hoang%2C+C+H">Chi Hieu Hoang</a>, <a href="/search/?searchtype=author&amp;query=Nguyen%2C+H+Q">Hung Quoc Nguyen</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="2410.20705v1-abstract-short" style="display: inline;"> Thermoelectricity in telluride materials is often improved by replacing telluride with selenium in its crystal. Most work, however, focuses on bulk crystal and leaves the 2D thin films intact. In this paper, we optimize the fabrication of selenium-doped bismuth telluride (Bi$_2$Te$_{3-\rm{x}}$Se$_{\rm{x}}$) thin films using a 3-source thermal co-evaporation. Thermoelectric properties, including th&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2410.20705v1-abstract-full').style.display = 'inline'; document.getElementById('2410.20705v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2410.20705v1-abstract-full" style="display: none;"> Thermoelectricity in telluride materials is often improved by replacing telluride with selenium in its crystal. Most work, however, focuses on bulk crystal and leaves the 2D thin films intact. In this paper, we optimize the fabrication of selenium-doped bismuth telluride (Bi$_2$Te$_{3-\rm{x}}$Se$_{\rm{x}}$) thin films using a 3-source thermal co-evaporation. Thermoelectric properties, including the Seebeck coefficient and electrical resistivity, are systematically characterized to evaluate the material&#39;s performance for thermoelectric applications near room temperature. The thin films were deposited under carefully controlled conditions, with the evaporation rates of bismuth, tellurium, and selenium precisely monitored to achieve the desired stoichiometry and crystalline phase. Finally, thermoelectricity in Bi$_2$Te$_{3-\rm{x}}$Se$_{\rm{x}}$ at the ultra-thin regime is investigated. We consistently obtain films with thickness near 30 nm with a Seebeck coefficient of 400 $渭$V/K and a power factor of 1 mW/mK$^2$. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2410.20705v1-abstract-full').style.display = 'none'; document.getElementById('2410.20705v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 27 October, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2410.02889">arXiv:2410.02889</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2410.02889">pdf</a>, <a href="https://arxiv.org/ps/2410.02889">ps</a>, <a href="https://arxiv.org/format/2410.02889">other</a>]&nbsp;</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> <p class="title is-5 mathjax"> Weighted estimates for a bilinear fractional integral operator and its commutator: A union condition </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+C">Cong Hoang</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="2410.02889v1-abstract-short" style="display: inline;"> The main theme of this paper is to give sufficient conditions for the weighted boundedness of the bilinear fractional integral operator $\mathsf{BI}_\al$. The proposed condition involves the union of multilinear Muckenhoupt-type conditions. We have achieved new results in an unknown case and remarkably improved other known results by utilizing the hidden convolution nature inside the operator. We&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2410.02889v1-abstract-full').style.display = 'inline'; document.getElementById('2410.02889v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2410.02889v1-abstract-full" style="display: none;"> The main theme of this paper is to give sufficient conditions for the weighted boundedness of the bilinear fractional integral operator $\mathsf{BI}_\al$. The proposed condition involves the union of multilinear Muckenhoupt-type conditions. We have achieved new results in an unknown case and remarkably improved other known results by utilizing the hidden convolution nature inside the operator. We also study the effects of the general product commutators on the main operator and the weighted estimates for a related maximal operator that norm-wise dominates the main operator. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2410.02889v1-abstract-full').style.display = 'none'; document.getElementById('2410.02889v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 3 October, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2408.11208">arXiv:2408.11208</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2408.11208">pdf</a>, <a href="https://arxiv.org/format/2408.11208">other</a>]&nbsp;</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="Machine Learning">cs.LG</span> </div> </div> <p class="title is-5 mathjax"> PooDLe: Pooled and dense self-supervised learning from naturalistic videos </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Wang%2C+A+N">Alex N. Wang</a>, <a href="/search/?searchtype=author&amp;query=Hoang%2C+C">Christopher Hoang</a>, <a href="/search/?searchtype=author&amp;query=Xiong%2C+Y">Yuwen Xiong</a>, <a href="/search/?searchtype=author&amp;query=LeCun%2C+Y">Yann LeCun</a>, <a href="/search/?searchtype=author&amp;query=Ren%2C+M">Mengye Ren</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="2408.11208v1-abstract-short" style="display: inline;"> Self-supervised learning has driven significant progress in learning from single-subject, iconic images. However, there are still unanswered questions about the use of minimally-curated, naturalistic video data, which contain dense scenes with many independent objects, imbalanced class distributions, and varying object sizes. In this paper, we propose a novel approach that combines an invariance-b&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2408.11208v1-abstract-full').style.display = 'inline'; document.getElementById('2408.11208v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2408.11208v1-abstract-full" style="display: none;"> Self-supervised learning has driven significant progress in learning from single-subject, iconic images. However, there are still unanswered questions about the use of minimally-curated, naturalistic video data, which contain dense scenes with many independent objects, imbalanced class distributions, and varying object sizes. In this paper, we propose a novel approach that combines an invariance-based SSL objective on pooled representations with a dense SSL objective that enforces equivariance to optical flow warping. Our findings indicate that a unified objective applied at multiple feature scales is essential for learning effective image representations from high-resolution, naturalistic videos. We validate our approach on the BDD100K driving video dataset and the Walking Tours first-person video dataset, demonstrating its ability to capture spatial understanding from a dense objective and semantic understanding via a pooled representation objective. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2408.11208v1-abstract-full').style.display = 'none'; document.getElementById('2408.11208v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 20 August, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 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">Project page: https://poodle-ssl.github.io</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2407.13803">arXiv:2407.13803</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2407.13803">pdf</a>, <a href="https://arxiv.org/format/2407.13803">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Cryptography and Security">cs.CR</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="Computation and Language">cs.CL</span> </div> </div> <p class="title is-5 mathjax"> Less is More: Sparse Watermarking in LLMs with Enhanced Text Quality </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+D+C">Duy C. Hoang</a>, <a href="/search/?searchtype=author&amp;query=Le%2C+H+T+Q">Hung T. Q. Le</a>, <a href="/search/?searchtype=author&amp;query=Chu%2C+R">Rui Chu</a>, <a href="/search/?searchtype=author&amp;query=Li%2C+P">Ping Li</a>, <a href="/search/?searchtype=author&amp;query=Zhao%2C+W">Weijie Zhao</a>, <a href="/search/?searchtype=author&amp;query=Lao%2C+Y">Yingjie Lao</a>, <a href="/search/?searchtype=author&amp;query=Doan%2C+K+D">Khoa D. Doan</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="2407.13803v1-abstract-short" style="display: inline;"> With the widespread adoption of Large Language Models (LLMs), concerns about potential misuse have emerged. To this end, watermarking has been adapted to LLM, enabling a simple and effective way to detect and monitor generated text. However, while the existing methods can differentiate between watermarked and unwatermarked text with high accuracy, they often face a trade-off between the quality of&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2407.13803v1-abstract-full').style.display = 'inline'; document.getElementById('2407.13803v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2407.13803v1-abstract-full" style="display: none;"> With the widespread adoption of Large Language Models (LLMs), concerns about potential misuse have emerged. To this end, watermarking has been adapted to LLM, enabling a simple and effective way to detect and monitor generated text. However, while the existing methods can differentiate between watermarked and unwatermarked text with high accuracy, they often face a trade-off between the quality of the generated text and the effectiveness of the watermarking process. In this work, we present a novel type of LLM watermark, Sparse Watermark, which aims to mitigate this trade-off by applying watermarks to a small subset of generated tokens distributed across the text. The key strategy involves anchoring watermarked tokens to words that have specific Part-of-Speech (POS) tags. Our experimental results demonstrate that the proposed watermarking scheme achieves high detectability while generating text that outperforms previous LLM watermarking methods in quality across various tasks <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2407.13803v1-abstract-full').style.display = 'none'; document.getElementById('2407.13803v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 17 July, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2407.10834">arXiv:2407.10834</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2407.10834">pdf</a>, <a href="https://arxiv.org/format/2407.10834">other</a>]&nbsp;</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="Artificial Intelligence">cs.AI</span> </div> </div> <p class="title is-5 mathjax"> MetaLLM: A High-performant and Cost-efficient Dynamic Framework for Wrapping LLMs </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Nguyen%2C+Q+H">Quang H. Nguyen</a>, <a href="/search/?searchtype=author&amp;query=Hoang%2C+D+C">Duy C. Hoang</a>, <a href="/search/?searchtype=author&amp;query=Decugis%2C+J">Juliette Decugis</a>, <a href="/search/?searchtype=author&amp;query=Manchanda%2C+S">Saurav Manchanda</a>, <a href="/search/?searchtype=author&amp;query=Chawla%2C+N+V">Nitesh V. Chawla</a>, <a href="/search/?searchtype=author&amp;query=Doan%2C+K+D">Khoa D. Doan</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="2407.10834v2-abstract-short" style="display: inline;"> The rapid progress in machine learning (ML) has brought forth many large language models (LLMs) that excel in various tasks and areas. These LLMs come with different abilities and costs in terms of computation or pricing. Since the demand for each query can vary, e.g., because of the queried domain or its complexity, defaulting to one LLM in an application is not usually the best choice, whether i&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2407.10834v2-abstract-full').style.display = 'inline'; document.getElementById('2407.10834v2-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2407.10834v2-abstract-full" style="display: none;"> The rapid progress in machine learning (ML) has brought forth many large language models (LLMs) that excel in various tasks and areas. These LLMs come with different abilities and costs in terms of computation or pricing. Since the demand for each query can vary, e.g., because of the queried domain or its complexity, defaulting to one LLM in an application is not usually the best choice, whether it is the biggest, priciest, or even the one with the best average test performance. Consequently, picking the right LLM that is both accurate and cost-effective for an application remains a challenge. In this paper, we introduce MetaLLM, a framework that dynamically and intelligently routes each query to the optimal LLM (among several available LLMs) for classification tasks, achieving significantly improved accuracy and cost-effectiveness. By framing the selection problem as a multi-armed bandit, MetaLLM balances prediction accuracy and cost efficiency under uncertainty. Our experiments, conducted on popular LLM platforms such as OpenAI&#39;s GPT models, Amazon&#39;s Titan, Anthropic&#39;s Claude, and Meta&#39;s LLaMa, showcase MetaLLM&#39;s efficacy in real-world scenarios, laying the groundwork for future extensions beyond classification tasks. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2407.10834v2-abstract-full').style.display = 'none'; document.getElementById('2407.10834v2-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 24 July, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 15 July, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2407.08439">arXiv:2407.08439</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2407.08439">pdf</a>, <a href="https://arxiv.org/format/2407.08439">other</a>]&nbsp;</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 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/j.apnum.2025.01.002">10.1016/j.apnum.2025.01.002 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> A fitted space-time finite element method for an advection-diffusion problem with moving interfaces </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Nguyen%2C+Q+H">Quang Huy Nguyen</a>, <a href="/search/?searchtype=author&amp;query=Le%2C+V+C">Van Chien Le</a>, <a href="/search/?searchtype=author&amp;query=Hoang%2C+P+C">Phuong Cuc Hoang</a>, <a href="/search/?searchtype=author&amp;query=Ta%2C+T+T+M">Thi Thanh Mai Ta</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="2407.08439v2-abstract-short" style="display: inline;"> This paper presents a space-time interface-fitted finite element method for solving a parabolic advection-diffusion problem with a nonstationary interface. The jumping diffusion coefficient gives rise to the discontinuity of the solution gradient across the interface. We use the Banach-Necas-Babuska theorem to show the well-posedness of the continuous variational problem. A fully discrete finite-e&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2407.08439v2-abstract-full').style.display = 'inline'; document.getElementById('2407.08439v2-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2407.08439v2-abstract-full" style="display: none;"> This paper presents a space-time interface-fitted finite element method for solving a parabolic advection-diffusion problem with a nonstationary interface. The jumping diffusion coefficient gives rise to the discontinuity of the solution gradient across the interface. We use the Banach-Necas-Babuska theorem to show the well-posedness of the continuous variational problem. A fully discrete finite-element based scheme is analyzed using the Galerkin method and unstructured interface-fitted meshes. An optimal error estimate is established in a discrete energy norm under a globally low but locally high regularity condition. Some numerical results corroborate our theoretical results. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2407.08439v2-abstract-full').style.display = 'none'; document.getElementById('2407.08439v2-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 10 January, 2025; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 11 July, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 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">20 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/2406.18602">arXiv:2406.18602</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2406.18602">pdf</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Applications">stat.AP</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computation">stat.CO</span> </div> </div> <p class="title is-5 mathjax"> Multi-level Phenotypic Models of Cardiovascular Disease and Obstructive Sleep Apnea Comorbidities: A Longitudinal Wisconsin Sleep Cohort Study </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Nguyen%2C+D">Duy Nguyen</a>, <a href="/search/?searchtype=author&amp;query=Hoang%2C+C">Ca Hoang</a>, <a href="/search/?searchtype=author&amp;query=Huynh%2C+P+K">Phat K. Huynh</a>, <a href="/search/?searchtype=author&amp;query=Truong%2C+T">Tien Truong</a>, <a href="/search/?searchtype=author&amp;query=Nguyen%2C+D">Dang Nguyen</a>, <a href="/search/?searchtype=author&amp;query=Sharma%2C+A">Abhay Sharma</a>, <a href="/search/?searchtype=author&amp;query=Le%2C+T+Q">Trung Q. Le</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="2406.18602v1-abstract-short" style="display: inline;"> Cardiovascular diseases (CVDs) are notably prevalent among patients with obstructive sleep apnea (OSA), posing unique challenges in predicting CVD progression due to the intricate interactions of comorbidities. Traditional models typically lack the necessary dynamic and longitudinal scope to accurately forecast CVD trajectories in OSA patients. This study introduces a novel multi-level phenotypic&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2406.18602v1-abstract-full').style.display = 'inline'; document.getElementById('2406.18602v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2406.18602v1-abstract-full" style="display: none;"> Cardiovascular diseases (CVDs) are notably prevalent among patients with obstructive sleep apnea (OSA), posing unique challenges in predicting CVD progression due to the intricate interactions of comorbidities. Traditional models typically lack the necessary dynamic and longitudinal scope to accurately forecast CVD trajectories in OSA patients. This study introduces a novel multi-level phenotypic model to analyze the progression and interplay of these conditions over time, utilizing data from the Wisconsin Sleep Cohort, which includes 1,123 participants followed for decades. Our methodology comprises three advanced steps: (1) Conducting feature importance analysis through tree-based models to underscore critical predictive variables like total cholesterol, low-density lipoprotein (LDL), and diabetes. (2) Developing a logistic mixed-effects model (LGMM) to track longitudinal transitions and pinpoint significant factors, which displayed a diagnostic accuracy of 0.9556. (3) Implementing t-distributed Stochastic Neighbor Embedding (t-SNE) alongside Gaussian Mixture Models (GMM) to segment patient data into distinct phenotypic clusters that reflect varied risk profiles and disease progression pathways. This phenotypic clustering revealed two main groups, with one showing a markedly increased risk of major adverse cardiovascular events (MACEs), underscored by the significant predictive role of nocturnal hypoxia and sympathetic nervous system activity from sleep data. Analysis of transitions and trajectories with t-SNE and GMM highlighted different progression rates within the cohort, with one cluster progressing more slowly towards severe CVD states than the other. This study offers a comprehensive understanding of the dynamic relationship between CVD and OSA, providing valuable tools for predicting disease onset and tailoring treatment approaches. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2406.18602v1-abstract-full').style.display = 'none'; document.getElementById('2406.18602v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 19 June, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 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">30 pages, 5 figure, 5 tables</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2406.13772">arXiv:2406.13772</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2406.13772">pdf</a>, <a href="https://arxiv.org/ps/2406.13772">ps</a>, <a href="https://arxiv.org/format/2406.13772">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Classical Analysis and ODEs">math.CA</span> </div> </div> <p class="title is-5 mathjax"> A new look at subrepresentation formulas </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+C">Cong Hoang</a>, <a href="/search/?searchtype=author&amp;query=Moen%2C+K">Kabe Moen</a>, <a href="/search/?searchtype=author&amp;query=P%C3%A9rez%2C+C">Carlos P茅rez</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="2406.13772v1-abstract-short" style="display: inline;"> We extend the subrepresentation formula $$ |f(x)|\le c_n\,I_1(|\nabla f|)(x) $$ in several ways. First, we consider more general $A_1$-potential operators on the right-hand side and prove local and global pointwise inequalities for these operators. Second, we show that we can improve the right-hand side using fractional derivatives. Finally, we extend our results to rough singular integral operato&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2406.13772v1-abstract-full').style.display = 'inline'; document.getElementById('2406.13772v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2406.13772v1-abstract-full" style="display: none;"> We extend the subrepresentation formula $$ |f(x)|\le c_n\,I_1(|\nabla f|)(x) $$ in several ways. First, we consider more general $A_1$-potential operators on the right-hand side and prove local and global pointwise inequalities for these operators. Second, we show that we can improve the right-hand side using fractional derivatives. Finally, we extend our results to rough singular integral operators, similar to the main result in [HMP1]. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2406.13772v1-abstract-full').style.display = 'none'; document.getElementById('2406.13772v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 19 June, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2401.09611">arXiv:2401.09611</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2401.09611">pdf</a>, <a href="https://arxiv.org/ps/2401.09611">ps</a>, <a href="https://arxiv.org/format/2401.09611">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Classical Analysis and ODEs">math.CA</span> </div> </div> <p class="title is-5 mathjax"> New pointwise bounds by Riesz potential type operators </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+C">Cong Hoang</a>, <a href="/search/?searchtype=author&amp;query=Moen%2C+K">Kabe Moen</a>, <a href="/search/?searchtype=author&amp;query=P%C3%A9rez%2C+C">Carlos P茅rez</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="2401.09611v1-abstract-short" style="display: inline;"> We investigate new pointwise bounds for a class of rough integral operators, $T_{惟,伪}$, for a parameter $0&lt;伪&lt;n$ that includes classical rough singular integrals of Calder贸n and Zygmund, rough hypersingular integrals, and rough fractional integral operators. We prove that the rough integral operators are bounded by a sparse potential operator that depends on the size of the symbol $惟$. As a result&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2401.09611v1-abstract-full').style.display = 'inline'; document.getElementById('2401.09611v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2401.09611v1-abstract-full" style="display: none;"> We investigate new pointwise bounds for a class of rough integral operators, $T_{惟,伪}$, for a parameter $0&lt;伪&lt;n$ that includes classical rough singular integrals of Calder贸n and Zygmund, rough hypersingular integrals, and rough fractional integral operators. We prove that the rough integral operators are bounded by a sparse potential operator that depends on the size of the symbol $惟$. As a result of our pointwise inequalities, we obtain several new Sobolev mappings of the form $T_{惟,伪}:\dot W^{1,p}\rightarrow L^q$ <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2401.09611v1-abstract-full').style.display = 'none'; document.getElementById('2401.09611v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 17 January, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2310.16234">arXiv:2310.16234</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2310.16234">pdf</a>, <a href="https://arxiv.org/format/2310.16234">other</a>]&nbsp;</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 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/j.engappai.2023.107327">10.1016/j.engappai.2023.107327 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Pixel-Level Clustering Network for Unsupervised Image Segmentation </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+C+M">Cuong Manh Hoang</a>, <a href="/search/?searchtype=author&amp;query=Kang%2C+B">Byeongkeun Kang</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="2310.16234v1-abstract-short" style="display: inline;"> While image segmentation is crucial in various computer vision applications, such as autonomous driving, grasping, and robot navigation, annotating all objects at the pixel-level for training is nearly impossible. Therefore, the study of unsupervised image segmentation methods is essential. In this paper, we present a pixel-level clustering framework for segmenting images into regions without usin&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2310.16234v1-abstract-full').style.display = 'inline'; document.getElementById('2310.16234v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2310.16234v1-abstract-full" style="display: none;"> While image segmentation is crucial in various computer vision applications, such as autonomous driving, grasping, and robot navigation, annotating all objects at the pixel-level for training is nearly impossible. Therefore, the study of unsupervised image segmentation methods is essential. In this paper, we present a pixel-level clustering framework for segmenting images into regions without using ground truth annotations. The proposed framework includes feature embedding modules with an attention mechanism, a feature statistics computing module, image reconstruction, and superpixel segmentation to achieve accurate unsupervised segmentation. Additionally, we propose a training strategy that utilizes intra-consistency within each superpixel, inter-similarity/dissimilarity between neighboring superpixels, and structural similarity between images. To avoid potential over-segmentation caused by superpixel-based losses, we also propose a post-processing method. Furthermore, we present an extension of the proposed method for unsupervised semantic segmentation. We conducted experiments on three publicly available datasets (Berkeley segmentation dataset, PASCAL VOC 2012 dataset, and COCO-Stuff dataset) to demonstrate the effectiveness of the proposed framework. The experimental results show that the proposed framework outperforms previous state-of-the-art methods. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2310.16234v1-abstract-full').style.display = 'none'; document.getElementById('2310.16234v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 24 October, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2023. </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">13 pages</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Engineering Applications of Artificial Intelligence, Volume 127, Part B, 2024 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2310.01452">arXiv:2310.01452</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2310.01452">pdf</a>, <a href="https://arxiv.org/format/2310.01452">other</a>]&nbsp;</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"> Fooling the Textual Fooler via Randomizing Latent Representations </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+D+C">Duy C. Hoang</a>, <a href="/search/?searchtype=author&amp;query=Nguyen%2C+Q+H">Quang H. Nguyen</a>, <a href="/search/?searchtype=author&amp;query=Manchanda%2C+S">Saurav Manchanda</a>, <a href="/search/?searchtype=author&amp;query=Peng%2C+M">MinLong Peng</a>, <a href="/search/?searchtype=author&amp;query=Wong%2C+K">Kok-Seng Wong</a>, <a href="/search/?searchtype=author&amp;query=Doan%2C+K+D">Khoa D. Doan</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="2310.01452v2-abstract-short" style="display: inline;"> Despite outstanding performance in a variety of NLP tasks, recent studies have revealed that NLP models are vulnerable to adversarial attacks that slightly perturb the input to cause the models to misbehave. Among these attacks, adversarial word-level perturbations are well-studied and effective attack strategies. Since these attacks work in black-box settings, they do not require access to the mo&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2310.01452v2-abstract-full').style.display = 'inline'; document.getElementById('2310.01452v2-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2310.01452v2-abstract-full" style="display: none;"> Despite outstanding performance in a variety of NLP tasks, recent studies have revealed that NLP models are vulnerable to adversarial attacks that slightly perturb the input to cause the models to misbehave. Among these attacks, adversarial word-level perturbations are well-studied and effective attack strategies. Since these attacks work in black-box settings, they do not require access to the model architecture or model parameters and thus can be detrimental to existing NLP applications. To perform an attack, the adversary queries the victim model many times to determine the most important words in an input text and to replace these words with their corresponding synonyms. In this work, we propose a lightweight and attack-agnostic defense whose main goal is to perplex the process of generating an adversarial example in these query-based black-box attacks; that is to fool the textual fooler. This defense, named AdvFooler, works by randomizing the latent representation of the input at inference time. Different from existing defenses, AdvFooler does not necessitate additional computational overhead during training nor relies on assumptions about the potential adversarial perturbation set while having a negligible impact on the model&#39;s accuracy. Our theoretical and empirical analyses highlight the significance of robustness resulting from confusing the adversary via randomizing the latent space, as well as the impact of randomization on clean accuracy. Finally, we empirically demonstrate near state-of-the-art robustness of AdvFooler against representative adversarial word-level attacks on two benchmark datasets. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2310.01452v2-abstract-full').style.display = 'none'; document.getElementById('2310.01452v2-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 9 June, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 2 October, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2023. </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">Accepted to Findings of ACL 2024</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2309.03232">arXiv:2309.03232</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2309.03232">pdf</a>, <a href="https://arxiv.org/format/2309.03232">other</a>]&nbsp;</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="Computer Vision and Pattern Recognition">cs.CV</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> </div> </div> <p class="title is-5 mathjax"> Retail store customer behavior analysis system: Design and Implementation </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Nguyen%2C+T+D">Tuan Dinh Nguyen</a>, <a href="/search/?searchtype=author&amp;query=Hihara%2C+K">Keisuke Hihara</a>, <a href="/search/?searchtype=author&amp;query=Hoang%2C+T+C">Tung Cao Hoang</a>, <a href="/search/?searchtype=author&amp;query=Utada%2C+Y">Yumeka Utada</a>, <a href="/search/?searchtype=author&amp;query=Torii%2C+A">Akihiko Torii</a>, <a href="/search/?searchtype=author&amp;query=Izumi%2C+N">Naoki Izumi</a>, <a href="/search/?searchtype=author&amp;query=Thuy%2C+N+T">Nguyen Thanh Thuy</a>, <a href="/search/?searchtype=author&amp;query=Tran%2C+L+Q">Long Quoc Tran</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="2309.03232v1-abstract-short" style="display: inline;"> Understanding customer behavior in retail stores plays a crucial role in improving customer satisfaction by adding personalized value to services. Behavior analysis reveals both general and detailed patterns in the interaction of customers with a store items and other people, providing store managers with insight into customer preferences. Several solutions aim to utilize this data by recognizing&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2309.03232v1-abstract-full').style.display = 'inline'; document.getElementById('2309.03232v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2309.03232v1-abstract-full" style="display: none;"> Understanding customer behavior in retail stores plays a crucial role in improving customer satisfaction by adding personalized value to services. Behavior analysis reveals both general and detailed patterns in the interaction of customers with a store items and other people, providing store managers with insight into customer preferences. Several solutions aim to utilize this data by recognizing specific behaviors through statistical visualization. However, current approaches are limited to the analysis of small customer behavior sets, utilizing conventional methods to detect behaviors. They do not use deep learning techniques such as deep neural networks, which are powerful methods in the field of computer vision. Furthermore, these methods provide limited figures when visualizing the behavioral data acquired by the system. In this study, we propose a framework that includes three primary parts: mathematical modeling of customer behaviors, behavior analysis using an efficient deep learning based system, and individual and group behavior visualization. Each module and the entire system were validated using data from actual situations in a retail store. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2309.03232v1-abstract-full').style.display = 'none'; document.getElementById('2309.03232v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 5 September, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> September 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2307.15594">arXiv:2307.15594</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2307.15594">pdf</a>, <a href="https://arxiv.org/ps/2307.15594">ps</a>, <a href="https://arxiv.org/format/2307.15594">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Classical Analysis and ODEs">math.CA</span> </div> </div> <p class="title is-5 mathjax"> A homage to Guido Weiss and his leadership of the Saint Louis team: Commutators of Singular Integrals and Sobolev inequalities </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+C">Cong Hoang</a>, <a href="/search/?searchtype=author&amp;query=Moen%2C+K">Kabe Moen</a>, <a href="/search/?searchtype=author&amp;query=P%C3%A9rez%2C+C">Carlos P茅rez</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="2307.15594v1-abstract-short" style="display: inline;"> We extend some classical Sobolev-type inequalities for linear and non-linear commutators. </span> <span class="abstract-full has-text-grey-dark mathjax" id="2307.15594v1-abstract-full" style="display: none;"> We extend some classical Sobolev-type inequalities for linear and non-linear commutators. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2307.15594v1-abstract-full').style.display = 'none'; document.getElementById('2307.15594v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 28 July, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2307.15180">arXiv:2307.15180</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2307.15180">pdf</a>, <a href="https://arxiv.org/format/2307.15180">other</a>]&nbsp;</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="Cryptography and Security">cs.CR</span> </div> </div> <p class="title is-5 mathjax"> EnSolver: Uncertainty-Aware Ensemble CAPTCHA Solvers with Theoretical Guarantees </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+D+C">Duc C. Hoang</a>, <a href="/search/?searchtype=author&amp;query=Ousat%2C+B">Behzad Ousat</a>, <a href="/search/?searchtype=author&amp;query=Kharraz%2C+A">Amin Kharraz</a>, <a href="/search/?searchtype=author&amp;query=Nguyen%2C+C+V">Cuong V. Nguyen</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="2307.15180v2-abstract-short" style="display: inline;"> The popularity of text-based CAPTCHA as a security mechanism to protect websites from automated bots has prompted researches in CAPTCHA solvers, with the aim of understanding its failure cases and subsequently making CAPTCHAs more secure. Recently proposed solvers, built on advances in deep learning, are able to crack even the very challenging CAPTCHAs with high accuracy. However, these solvers of&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2307.15180v2-abstract-full').style.display = 'inline'; document.getElementById('2307.15180v2-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2307.15180v2-abstract-full" style="display: none;"> The popularity of text-based CAPTCHA as a security mechanism to protect websites from automated bots has prompted researches in CAPTCHA solvers, with the aim of understanding its failure cases and subsequently making CAPTCHAs more secure. Recently proposed solvers, built on advances in deep learning, are able to crack even the very challenging CAPTCHAs with high accuracy. However, these solvers often perform poorly on out-of-distribution samples that contain visual features different from those in the training set. Furthermore, they lack the ability to detect and avoid such samples, making them susceptible to being locked out by defense systems after a certain number of failed attempts. In this paper, we propose EnSolver, a family of CAPTCHA solvers that use deep ensemble uncertainty to detect and skip out-of-distribution CAPTCHAs, making it harder to be detected. We prove novel theoretical bounds on the effectiveness of our solvers and demonstrate their use with state-of-the-art CAPTCHA solvers. Our experiments show that the proposed approaches perform well when cracking CAPTCHA datasets that contain both in-distribution and out-of-distribution samples. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2307.15180v2-abstract-full').style.display = 'none'; document.getElementById('2307.15180v2-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 28 June, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 27 July, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2023. </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">A previous version of this paper was presented at the Epistemic Uncertainty - E-pi UAI 2023 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/2307.10417">arXiv:2307.10417</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2307.10417">pdf</a>, <a href="https://arxiv.org/ps/2307.10417">ps</a>, <a href="https://arxiv.org/format/2307.10417">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Classical Analysis and ODEs">math.CA</span> </div> </div> <p class="title is-5 mathjax"> Pointwise estimates for rough operators with applications to Sobolev inequalities </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+C">Cong Hoang</a>, <a href="/search/?searchtype=author&amp;query=Moen%2C+K">Kabe Moen</a>, <a href="/search/?searchtype=author&amp;query=P%C3%A9rez%2C+C">Carlos P茅rez</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="2307.10417v2-abstract-short" style="display: inline;"> We investigate Sobolev inequalities for several rough operators. We prove that several operators satisfy a pointwise bound by the Riesz potential applied to the gradient. From this inequality, we derive several new Sobolev-type inequalities with an operator on the left-hand side. </span> <span class="abstract-full has-text-grey-dark mathjax" id="2307.10417v2-abstract-full" style="display: none;"> We investigate Sobolev inequalities for several rough operators. We prove that several operators satisfy a pointwise bound by the Riesz potential applied to the gradient. From this inequality, we derive several new Sobolev-type inequalities with an operator on the left-hand side. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2307.10417v2-abstract-full').style.display = 'none'; document.getElementById('2307.10417v2-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 3 January, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 19 July, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2023. </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">v2: typos corrected</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2306.03376">arXiv:2306.03376</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2306.03376">pdf</a>, <a href="https://arxiv.org/ps/2306.03376">ps</a>, <a href="https://arxiv.org/format/2306.03376">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Combinatorics">math.CO</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Discrete Mathematics">cs.DM</span> </div> </div> <p class="title is-5 mathjax"> Infinite families of $k$-vertex-critical ($P_5$, $C_5$)-free graphs </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Cameron%2C+B">Ben Cameron</a>, <a href="/search/?searchtype=author&amp;query=Ho%C3%A0ng%2C+C+T">Ch铆nh T. Ho脿ng</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="2306.03376v1-abstract-short" style="display: inline;"> A graph is $k$-vertex-critical if $蠂(G)=k$ but $蠂(G-v)&lt;k$ for all $v\in V(G)$. We construct a new infinite families of $k$-vertex-critical $(P_5,C_5)$-free graphs for all $k\ge 6$. Our construction generalizes known constructions for $4$-vertex-critical $P_7$-free graphs and $5$-vertex-critical $P_5$-free graphs and is in contrast to the fact that there are only finitely many $5$-vertex-critical&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.03376v1-abstract-full').style.display = 'inline'; document.getElementById('2306.03376v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2306.03376v1-abstract-full" style="display: none;"> A graph is $k$-vertex-critical if $蠂(G)=k$ but $蠂(G-v)&lt;k$ for all $v\in V(G)$. We construct a new infinite families of $k$-vertex-critical $(P_5,C_5)$-free graphs for all $k\ge 6$. Our construction generalizes known constructions for $4$-vertex-critical $P_7$-free graphs and $5$-vertex-critical $P_5$-free graphs and is in contrast to the fact that there are only finitely many $5$-vertex-critical $(P_5,C_5)$-free graphs. In fact, our construction is actually even more well-structured, being $(2P_2,K_3+P_1,C_5)$-free. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.03376v1-abstract-full').style.display = 'none'; document.getElementById('2306.03376v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 5 June, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2303.03479">arXiv:2303.03479</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2303.03479">pdf</a>, <a href="https://arxiv.org/format/2303.03479">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Combinatorics">math.CO</span> </div> </div> <p class="title is-5 mathjax"> A Closure Lemma for tough graphs and Hamiltonian degree conditions </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+C+T">Chinh T. Hoang</a>, <a href="/search/?searchtype=author&amp;query=Robin%2C+C">Cleophee Robin</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="2303.03479v2-abstract-short" style="display: inline;"> The closure of a graph $G$ is the graph $G^*$ obtained from $G$ by repeatedly adding edges between pairs of non-adjacent vertices whose degree sum is at least $n$, where $n$ is the number of vertices of $G$. The well-known Closure Lemma proved by Bondy and Chv谩tal states that a graph $G$ is Hamiltonian if and only if its closure $G^*$ is. This lemma can be used to prove several classical results i&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2303.03479v2-abstract-full').style.display = 'inline'; document.getElementById('2303.03479v2-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2303.03479v2-abstract-full" style="display: none;"> The closure of a graph $G$ is the graph $G^*$ obtained from $G$ by repeatedly adding edges between pairs of non-adjacent vertices whose degree sum is at least $n$, where $n$ is the number of vertices of $G$. The well-known Closure Lemma proved by Bondy and Chv谩tal states that a graph $G$ is Hamiltonian if and only if its closure $G^*$ is. This lemma can be used to prove several classical results in Hamiltonian graph theory. We prove a version of the Closure Lemma for tough graphs. A graph $G$ is $t$-tough if for any set $S$ of vertices of $G$, the number of components of $G-S$ is at most $t |S|$. A Hamiltonian graph must necessarily be 1-tough. Conversely, Chv谩tal conjectured that there exists a constant $t$ such that every $t$-tough graph is Hamiltonian. The {\it $t$-closure} of a graph $G$ is the graph $G^{t*}$ obtained from $G$ by repeatedly adding edges between pairs of non-adjacent vertices whose degree sum is at least $n-t$. We prove that, for $t\geq 2$, a $\frac{3t-1}{2}$-tough graph $G$ is Hamiltonian if and only if its $t$-closure $G^{t*}$ is. Ho脿ng conjectured the following: Let $G$ be a graph with degree sequence $d_1 \leq d_2 \leq \ldots \leq d_n$; then $G$ is Hamiltonian if $G$ is $t$-tough and, $\forall i &lt;\frac{n}{2},\mbox{ if } d_i\leq i \mbox{ then } d_{n-i+t}\geq n-i$. This conjecture is analogous to the well known theorem of Chv谩tal on Hamiltonian ideals. Ho脿ng proved the conjecture for $t \leq 3$. Using the closure lemma for tough graphs, we prove the conjecture for $t = 4$. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2303.03479v2-abstract-full').style.display = 'none'; document.getElementById('2303.03479v2-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 29 November, 2023; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 6 March, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">MSC Class:</span> 05C45 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2302.06847">arXiv:2302.06847</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2302.06847">pdf</a>, <a href="https://arxiv.org/format/2302.06847">other</a>]&nbsp;</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> </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/10.1088/1361-6501/acde9c">10.1088/1361-6501/acde9c <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> An in-situ thermoelectric measurement apparatus inside a thermal-evaporator </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Nguyen%2C+K+T">Kien Trung Nguyen</a>, <a href="/search/?searchtype=author&amp;query=Bui-Thanh%2C+G">Giang Bui-Thanh</a>, <a href="/search/?searchtype=author&amp;query=Pham%2C+H+T">Hong Thi Pham</a>, <a href="/search/?searchtype=author&amp;query=Nguyen-Tran%2C+T">Thuat Nguyen-Tran</a>, <a href="/search/?searchtype=author&amp;query=Hoang%2C+C+H">Chi Hieu Hoang</a>, <a href="/search/?searchtype=author&amp;query=Nguyen%2C+H+Q">Hung Q. Nguyen</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="2302.06847v2-abstract-short" style="display: inline;"> At the ultra-thin limit below 20 nm, a film&#39;s electrical conductivity, thermal conductivity, or thermoelectricity depends heavily on its thickness. In most studies, each sample is fabricated one at a time, potentially leading to considerable uncertainty in later characterizations. We design and build an in-situ apparatus to measure thermoelectricity during their deposition inside a thermal evapora&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2302.06847v2-abstract-full').style.display = 'inline'; document.getElementById('2302.06847v2-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2302.06847v2-abstract-full" style="display: none;"> At the ultra-thin limit below 20 nm, a film&#39;s electrical conductivity, thermal conductivity, or thermoelectricity depends heavily on its thickness. In most studies, each sample is fabricated one at a time, potentially leading to considerable uncertainty in later characterizations. We design and build an in-situ apparatus to measure thermoelectricity during their deposition inside a thermal evaporator. A temperature difference of up to 2 K is generated by a current passing through an on-chip resistor patterned using photolithography. The Seebeck voltage is measured on a Hall bar structure of a film deposited through a shadow mask. The measurement system is calibrated carefully before loading into the thermal evaporator. This in-situ thermoelectricity measurement system has been thoroughly tested on various materials, including Bi, Te, and Bi$_2$Te$_3$, at high temperatures up to 500 K. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2302.06847v2-abstract-full').style.display = 'none'; document.getElementById('2302.06847v2-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 20 June, 2023; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 14 February, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Measurement Science and Technology, 2023 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2212.04659">arXiv:2212.04659</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2212.04659">pdf</a>, <a href="https://arxiv.org/ps/2212.04659">ps</a>, <a href="https://arxiv.org/format/2212.04659">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Combinatorics">math.CO</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Discrete Mathematics">cs.DM</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Data Structures and Algorithms">cs.DS</span> </div> </div> <p class="title is-5 mathjax"> A refinement on the structure of vertex-critical ($P_5$, gem)-free graphs </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Cameron%2C+B">Ben Cameron</a>, <a href="/search/?searchtype=author&amp;query=Ho%C3%A0ng%2C+C+T">Ch铆nh T. Ho脿ng</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="2212.04659v1-abstract-short" style="display: inline;"> We give a new, stronger proof that there are only finitely many $k$-vertex-critical ($P_5$,~gem)-free graphs for all $k$. Our proof further refines the structure of these graphs and allows for the implementation of a simple exhaustive computer search to completely list all $6$- and $7$-vertex-critical $(P_5$, gem)-free graphs. Our results imply the existence of polynomial-time certifying algorithm&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2212.04659v1-abstract-full').style.display = 'inline'; document.getElementById('2212.04659v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2212.04659v1-abstract-full" style="display: none;"> We give a new, stronger proof that there are only finitely many $k$-vertex-critical ($P_5$,~gem)-free graphs for all $k$. Our proof further refines the structure of these graphs and allows for the implementation of a simple exhaustive computer search to completely list all $6$- and $7$-vertex-critical $(P_5$, gem)-free graphs. Our results imply the existence of polynomial-time certifying algorithms to decide the $k$-colourability of $(P_5$, gem)-free graphs for all $k$ where the certificate is either a $k$-colouring or a $(k+1)$-vertex-critical induced subgraph. Our complete lists for $k\le 7$ allow for the implementation of these algorithms for all $k\le 6$. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2212.04659v1-abstract-full').style.display = 'none'; document.getElementById('2212.04659v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 8 December, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> December 2022. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2211.11001">arXiv:2211.11001</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2211.11001">pdf</a>]&nbsp;</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"> F2SD: A dataset for end-to-end group detection algorithms </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+G">Giang Hoang</a>, <a href="/search/?searchtype=author&amp;query=Dinh%2C+T+N">Tuan Nguyen Dinh</a>, <a href="/search/?searchtype=author&amp;query=Hoang%2C+T+C">Tung Cao Hoang</a>, <a href="/search/?searchtype=author&amp;query=Duy%2C+S+L">Son Le Duy</a>, <a href="/search/?searchtype=author&amp;query=Hihara%2C+K">Keisuke Hihara</a>, <a href="/search/?searchtype=author&amp;query=Utada%2C+Y">Yumeka Utada</a>, <a href="/search/?searchtype=author&amp;query=Torii%2C+A">Akihiko Torii</a>, <a href="/search/?searchtype=author&amp;query=Izumi%2C+N">Naoki Izumi</a>, <a href="/search/?searchtype=author&amp;query=Quoc%2C+L+T">Long Tran Quoc</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="2211.11001v1-abstract-short" style="display: inline;"> The lack of large-scale datasets has been impeding the advance of deep learning approaches to the problem of F-formation detection. Moreover, most research works on this problem rely on input sensor signals of object location and orientation rather than image signals. To address this, we develop a new, large-scale dataset of simulated images for F-formation detection, called F-formation Simulation&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2211.11001v1-abstract-full').style.display = 'inline'; document.getElementById('2211.11001v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2211.11001v1-abstract-full" style="display: none;"> The lack of large-scale datasets has been impeding the advance of deep learning approaches to the problem of F-formation detection. Moreover, most research works on this problem rely on input sensor signals of object location and orientation rather than image signals. To address this, we develop a new, large-scale dataset of simulated images for F-formation detection, called F-formation Simulation Dataset (F2SD). F2SD contains nearly 60,000 images simulated from GTA-5, with bounding boxes and orientation information on images, making it useful for a wide variety of modelling approaches. It is also closer to practical scenarios, where three-dimensional location and orientation information are costly to record. It is challenging to construct such a large-scale simulated dataset while keeping it realistic. Furthermore, the available research utilizes conventional methods to detect groups. They do not detect groups directly from the image. In this work, we propose (1) a large-scale simulation dataset F2SD and a pipeline for F-formation simulation, (2) a first-ever end-to-end baseline model for the task, and experiments on our simulation dataset. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2211.11001v1-abstract-full').style.display = 'none'; document.getElementById('2211.11001v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 20 November, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2022. </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">Accepted at ICMV 2022</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2210.05059">arXiv:2210.05059</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2210.05059">pdf</a>, <a href="https://arxiv.org/format/2210.05059">other</a>]&nbsp;</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"> Improving Robustness of Retrieval Augmented Translation via Shuffling of Suggestions </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+C">Cuong Hoang</a>, <a href="/search/?searchtype=author&amp;query=Sachan%2C+D">Devendra Sachan</a>, <a href="/search/?searchtype=author&amp;query=Mathur%2C+P">Prashant Mathur</a>, <a href="/search/?searchtype=author&amp;query=Thompson%2C+B">Brian Thompson</a>, <a href="/search/?searchtype=author&amp;query=Federico%2C+M">Marcello Federico</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="2210.05059v1-abstract-short" style="display: inline;"> Several recent studies have reported dramatic performance improvements in neural machine translation (NMT) by augmenting translation at inference time with fuzzy-matches retrieved from a translation memory (TM). However, these studies all operate under the assumption that the TMs available at test time are highly relevant to the testset. We demonstrate that for existing retrieval augmented transla&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2210.05059v1-abstract-full').style.display = 'inline'; document.getElementById('2210.05059v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2210.05059v1-abstract-full" style="display: none;"> Several recent studies have reported dramatic performance improvements in neural machine translation (NMT) by augmenting translation at inference time with fuzzy-matches retrieved from a translation memory (TM). However, these studies all operate under the assumption that the TMs available at test time are highly relevant to the testset. We demonstrate that for existing retrieval augmented translation methods, using a TM with a domain mismatch to the test set can result in substantially worse performance compared to not using a TM at all. We propose a simple method to expose fuzzy-match NMT systems during training and show that it results in a system that is much more tolerant (regaining up to 5.8 BLEU) to inference with TMs with domain mismatch. Also, the model is still competitive to the baseline when fed with suggestions from relevant TMs. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2210.05059v1-abstract-full').style.display = 'none'; document.getElementById('2210.05059v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 10 October, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2022. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2210.05047">arXiv:2210.05047</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2210.05047">pdf</a>, <a href="https://arxiv.org/format/2210.05047">other</a>]&nbsp;</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"> Improving Retrieval Augmented Neural Machine Translation by Controlling Source and Fuzzy-Match Interactions </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+C">Cuong Hoang</a>, <a href="/search/?searchtype=author&amp;query=Sachan%2C+D">Devendra Sachan</a>, <a href="/search/?searchtype=author&amp;query=Mathur%2C+P">Prashant Mathur</a>, <a href="/search/?searchtype=author&amp;query=Thompson%2C+B">Brian Thompson</a>, <a href="/search/?searchtype=author&amp;query=Federico%2C+M">Marcello Federico</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="2210.05047v1-abstract-short" style="display: inline;"> We explore zero-shot adaptation, where a general-domain model has access to customer or domain specific parallel data at inference time, but not during training. We build on the idea of Retrieval Augmented Translation (RAT) where top-k in-domain fuzzy matches are found for the source sentence, and target-language translations of those fuzzy-matched sentences are provided to the translation model a&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2210.05047v1-abstract-full').style.display = 'inline'; document.getElementById('2210.05047v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2210.05047v1-abstract-full" style="display: none;"> We explore zero-shot adaptation, where a general-domain model has access to customer or domain specific parallel data at inference time, but not during training. We build on the idea of Retrieval Augmented Translation (RAT) where top-k in-domain fuzzy matches are found for the source sentence, and target-language translations of those fuzzy-matched sentences are provided to the translation model at inference time. We propose a novel architecture to control interactions between a source sentence and the top-k fuzzy target-language matches, and compare it to architectures from prior work. We conduct experiments in two language pairs (En-De and En-Fr) by training models on WMT data and testing them with five and seven multi-domain datasets, respectively. Our approach consistently outperforms the alternative architectures, improving BLEU across language pair, domain, and number k of fuzzy matches. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2210.05047v1-abstract-full').style.display = 'none'; document.getElementById('2210.05047v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 10 October, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2022. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2207.05851">arXiv:2207.05851</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2207.05851">pdf</a>, <a href="https://arxiv.org/ps/2207.05851">ps</a>, <a href="https://arxiv.org/format/2207.05851">other</a>]&nbsp;</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"> Sockeye 3: Fast Neural Machine Translation with PyTorch </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hieber%2C+F">Felix Hieber</a>, <a href="/search/?searchtype=author&amp;query=Denkowski%2C+M">Michael Denkowski</a>, <a href="/search/?searchtype=author&amp;query=Domhan%2C+T">Tobias Domhan</a>, <a href="/search/?searchtype=author&amp;query=Barros%2C+B+D">Barbara Darques Barros</a>, <a href="/search/?searchtype=author&amp;query=Ye%2C+C+D">Celina Dong Ye</a>, <a href="/search/?searchtype=author&amp;query=Niu%2C+X">Xing Niu</a>, <a href="/search/?searchtype=author&amp;query=Hoang%2C+C">Cuong Hoang</a>, <a href="/search/?searchtype=author&amp;query=Tran%2C+K">Ke Tran</a>, <a href="/search/?searchtype=author&amp;query=Hsu%2C+B">Benjamin Hsu</a>, <a href="/search/?searchtype=author&amp;query=Nadejde%2C+M">Maria Nadejde</a>, <a href="/search/?searchtype=author&amp;query=Lakew%2C+S">Surafel Lakew</a>, <a href="/search/?searchtype=author&amp;query=Mathur%2C+P">Prashant Mathur</a>, <a href="/search/?searchtype=author&amp;query=Currey%2C+A">Anna Currey</a>, <a href="/search/?searchtype=author&amp;query=Federico%2C+M">Marcello Federico</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="2207.05851v4-abstract-short" style="display: inline;"> Sockeye 3 is the latest version of the Sockeye toolkit for Neural Machine Translation (NMT). Now based on PyTorch, Sockeye 3 provides faster model implementations and more advanced features with a further streamlined codebase. This enables broader experimentation with faster iteration, efficient training of stronger and faster models, and the flexibility to move new ideas quickly from research to&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2207.05851v4-abstract-full').style.display = 'inline'; document.getElementById('2207.05851v4-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2207.05851v4-abstract-full" style="display: none;"> Sockeye 3 is the latest version of the Sockeye toolkit for Neural Machine Translation (NMT). Now based on PyTorch, Sockeye 3 provides faster model implementations and more advanced features with a further streamlined codebase. This enables broader experimentation with faster iteration, efficient training of stronger and faster models, and the flexibility to move new ideas quickly from research to production. When running comparable models, Sockeye 3 is up to 126% faster than other PyTorch implementations on GPUs and up to 292% faster on CPUs. Sockeye 3 is open source software released under the Apache 2.0 license. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2207.05851v4-abstract-full').style.display = 'none'; document.getElementById('2207.05851v4-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 2 August, 2022; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 12 July, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2022. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2206.03422">arXiv:2206.03422</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2206.03422">pdf</a>, <a href="https://arxiv.org/ps/2206.03422">ps</a>, <a href="https://arxiv.org/format/2206.03422">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Combinatorics">math.CO</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Discrete Mathematics">cs.DM</span> </div> </div> <p class="title is-5 mathjax"> Vertex-critical $(P_3+\ell P_1)$-free and vertex-critical (gem, co-gem)-free graphs </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Abuadas%2C+T">Tala Abuadas</a>, <a href="/search/?searchtype=author&amp;query=Cameron%2C+B">Ben Cameron</a>, <a href="/search/?searchtype=author&amp;query=Ho%C3%A0ng%2C+C+T">Ch铆nh T. Ho脿ng</a>, <a href="/search/?searchtype=author&amp;query=Sawada%2C+J">Joe Sawada</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="2206.03422v1-abstract-short" style="display: inline;"> A graph $G$ is $k$-vertex-critical if $蠂(G)=k$ but $蠂(G-v)&lt;k$ for all $v\in V(G)$ where $蠂(G)$ denotes the chromatic number of $G$. We show that there are only finitely many $k$-critical $(P_3+\ell P_1)$-free graphs for all $k$ and all $\ell$. Together with previous results, the only graphs $H$ for which it is unknown if there are an infinite number of $k$-vertex-critical $H$-free graphs is&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2206.03422v1-abstract-full').style.display = 'inline'; document.getElementById('2206.03422v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2206.03422v1-abstract-full" style="display: none;"> A graph $G$ is $k$-vertex-critical if $蠂(G)=k$ but $蠂(G-v)&lt;k$ for all $v\in V(G)$ where $蠂(G)$ denotes the chromatic number of $G$. We show that there are only finitely many $k$-critical $(P_3+\ell P_1)$-free graphs for all $k$ and all $\ell$. Together with previous results, the only graphs $H$ for which it is unknown if there are an infinite number of $k$-vertex-critical $H$-free graphs is $H=(P_4+\ell P_1)$ for all $\ell\ge 1$. We consider a restriction on the smallest open case, and show that there are only finitely many $k$-vertex-critical (gem, co-gem)-free graphs for all $k$, where gem$=\overline{P_4+P_1}$. To do this, we show the stronger result that every vertex-critical (gem, co-gem)-free graph is either complete or a clique expansion of $C_5$. This characterization allows us to give the complete list of all $k$-vertex-critical (gem, co-gem)-free graphs for all $k\le 16$ <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2206.03422v1-abstract-full').style.display = 'none'; document.getElementById('2206.03422v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 7 June, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2022. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2203.07742">arXiv:2203.07742</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2203.07742">pdf</a>, <a href="https://arxiv.org/format/2203.07742">other</a>]&nbsp;</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"> ViWOZ: A Multi-Domain Task-Oriented Dialogue Systems Dataset For Low-resource Language </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Van%2C+P+N">Phi Nguyen Van</a>, <a href="/search/?searchtype=author&amp;query=Hoang%2C+T+C">Tung Cao Hoang</a>, <a href="/search/?searchtype=author&amp;query=Manh%2C+D+N">Dung Nguyen Manh</a>, <a href="/search/?searchtype=author&amp;query=Minh%2C+Q+N">Quan Nguyen Minh</a>, <a href="/search/?searchtype=author&amp;query=Quoc%2C+L+T">Long Tran Quoc</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="2203.07742v1-abstract-short" style="display: inline;"> Most of the current task-oriented dialogue systems (ToD), despite having interesting results, are designed for a handful of languages like Chinese and English. Therefore, their performance in low-resource languages is still a significant problem due to the absence of a standard dataset and evaluation policy. To address this problem, we proposed ViWOZ, a fully-annotated Vietnamese task-oriented dia&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.07742v1-abstract-full').style.display = 'inline'; document.getElementById('2203.07742v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2203.07742v1-abstract-full" style="display: none;"> Most of the current task-oriented dialogue systems (ToD), despite having interesting results, are designed for a handful of languages like Chinese and English. Therefore, their performance in low-resource languages is still a significant problem due to the absence of a standard dataset and evaluation policy. To address this problem, we proposed ViWOZ, a fully-annotated Vietnamese task-oriented dialogue dataset. ViWOZ is the first multi-turn, multi-domain tasked oriented dataset in Vietnamese, a low-resource language. The dataset consists of a total of 5,000 dialogues, including 60,946 fully annotated utterances. Furthermore, we provide a comprehensive benchmark of both modular and end-to-end models in low-resource language scenarios. With those characteristics, the ViWOZ dataset enables future studies on creating a multilingual task-oriented dialogue system. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2203.07742v1-abstract-full').style.display = 'none'; document.getElementById('2203.07742v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 15 March, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2022. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2112.09681">arXiv:2112.09681</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2112.09681">pdf</a>, <a href="https://arxiv.org/format/2112.09681">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Fluid Dynamics">physics.flu-dyn</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computational Physics">physics.comp-ph</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/j.cma.2022.115396">10.1016/j.cma.2022.115396 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Calibrating hypersonic turbulence flow models with the HIFiRE-1 experiment using data-driven machine-learned models </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Chowdhary%2C+K">Kenny Chowdhary</a>, <a href="/search/?searchtype=author&amp;query=Hoang%2C+C">Chi Hoang</a>, <a href="/search/?searchtype=author&amp;query=Lee%2C+K">Kookjin Lee</a>, <a href="/search/?searchtype=author&amp;query=Ray%2C+J">Jaideep Ray</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="2112.09681v1-abstract-short" style="display: inline;"> In this paper we study the efficacy of combining machine-learning methods with projection-based model reduction techniques for creating data-driven surrogate models of computationally expensive, high-fidelity physics models. Such surrogate models are essential for many-query applications e.g., engineering design optimization and parameter estimation, where it is necessary to invoke the high-fideli&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2112.09681v1-abstract-full').style.display = 'inline'; document.getElementById('2112.09681v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2112.09681v1-abstract-full" style="display: none;"> In this paper we study the efficacy of combining machine-learning methods with projection-based model reduction techniques for creating data-driven surrogate models of computationally expensive, high-fidelity physics models. Such surrogate models are essential for many-query applications e.g., engineering design optimization and parameter estimation, where it is necessary to invoke the high-fidelity model sequentially, many times. Surrogate models are usually constructed for individual scalar quantities. However there are scenarios where a spatially varying field needs to be modeled as a function of the model&#39;s input parameters. We develop a method to do so, using projections to represent spatial variability while a machine-learned model captures the dependence of the model&#39;s response on the inputs. The method is demonstrated on modeling the heat flux and pressure on the surface of the HIFiRE-1 geometry in a Mach 7.16 turbulent flow. The surrogate model is then used to perform Bayesian estimation of freestream conditions and parameters of the SST (Shear Stress Transport) turbulence model embedded in the high-fidelity (Reynolds-Averaged Navier-Stokes) flow simulator, using wind-tunnel data. The paper provides the first-ever Bayesian calibration of a turbulence model for complex hypersonic turbulent flows. We find that the primary issues in estimating the SST model parameters are the limited information content of the heat flux and pressure measurements and the large model-form error encountered in a certain part of the flow. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2112.09681v1-abstract-full').style.display = 'none'; document.getElementById('2112.09681v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 17 December, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> December 2021. </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">50 pages, research paper</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2111.09858">arXiv:2111.09858</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2111.09858">pdf</a>, <a href="https://arxiv.org/format/2111.09858">other</a>]&nbsp;</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="Artificial Intelligence">cs.AI</span> <span class="tag is-small is-grey 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="Robotics">cs.RO</span> </div> </div> <p class="title is-5 mathjax"> Successor Feature Landmarks for Long-Horizon Goal-Conditioned Reinforcement Learning </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+C">Christopher Hoang</a>, <a href="/search/?searchtype=author&amp;query=Sohn%2C+S">Sungryull Sohn</a>, <a href="/search/?searchtype=author&amp;query=Choi%2C+J">Jongwook Choi</a>, <a href="/search/?searchtype=author&amp;query=Carvalho%2C+W">Wilka Carvalho</a>, <a href="/search/?searchtype=author&amp;query=Lee%2C+H">Honglak Lee</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="2111.09858v1-abstract-short" style="display: inline;"> Operating in the real-world often requires agents to learn about a complex environment and apply this understanding to achieve a breadth of goals. This problem, known as goal-conditioned reinforcement learning (GCRL), becomes especially challenging for long-horizon goals. Current methods have tackled this problem by augmenting goal-conditioned policies with graph-based planning algorithms. However&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2111.09858v1-abstract-full').style.display = 'inline'; document.getElementById('2111.09858v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2111.09858v1-abstract-full" style="display: none;"> Operating in the real-world often requires agents to learn about a complex environment and apply this understanding to achieve a breadth of goals. This problem, known as goal-conditioned reinforcement learning (GCRL), becomes especially challenging for long-horizon goals. Current methods have tackled this problem by augmenting goal-conditioned policies with graph-based planning algorithms. However, they struggle to scale to large, high-dimensional state spaces and assume access to exploration mechanisms for efficiently collecting training data. In this work, we introduce Successor Feature Landmarks (SFL), a framework for exploring large, high-dimensional environments so as to obtain a policy that is proficient for any goal. SFL leverages the ability of successor features (SF) to capture transition dynamics, using it to drive exploration by estimating state-novelty and to enable high-level planning by abstracting the state-space as a non-parametric landmark-based graph. We further exploit SF to directly compute a goal-conditioned policy for inter-landmark traversal, which we use to execute plans to &#34;frontier&#34; landmarks at the edge of the explored state space. We show in our experiments on MiniGrid and ViZDoom that SFL enables efficient exploration of large, high-dimensional state spaces and outperforms state-of-the-art baselines on long-horizon GCRL tasks. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2111.09858v1-abstract-full').style.display = 'none'; document.getElementById('2111.09858v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 18 November, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2021. </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">NeurIPS 2021. Video and code at https://2016choang.github.io/sfl</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2110.15521">arXiv:2110.15521</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2110.15521">pdf</a>, <a href="https://arxiv.org/format/2110.15521">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Robotics">cs.RO</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> </div> </div> <p class="title is-5 mathjax"> ARviz -- An Augmented Reality-enabled Visualization Platform for ROS Applications </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+K+C">Khoa C. Hoang</a>, <a href="/search/?searchtype=author&amp;query=Chan%2C+W+P">Wesley P. Chan</a>, <a href="/search/?searchtype=author&amp;query=Lay%2C+S">Steven Lay</a>, <a href="/search/?searchtype=author&amp;query=Cosgun%2C+A">Akansel Cosgun</a>, <a href="/search/?searchtype=author&amp;query=Croft%2C+E+A">Elizabeth A. Croft</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="2110.15521v1-abstract-short" style="display: inline;"> Current robot interfaces such as teach pendants and 2D screen displays used for task visualization and interaction often seem unintuitive and limited in terms of information flow. This compromises task efficiency as interacting with the interface can distract the user from the task at hand. Augmented Reality (AR) technology offers the capability to create visually rich displays and intuitive inter&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2110.15521v1-abstract-full').style.display = 'inline'; document.getElementById('2110.15521v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2110.15521v1-abstract-full" style="display: none;"> Current robot interfaces such as teach pendants and 2D screen displays used for task visualization and interaction often seem unintuitive and limited in terms of information flow. This compromises task efficiency as interacting with the interface can distract the user from the task at hand. Augmented Reality (AR) technology offers the capability to create visually rich displays and intuitive interaction elements in situ. In recent years, AR has shown promising potential to enable effective human-robot interaction. We introduce ARviz - a versatile, extendable AR visualization platform built for robot applications developed with the widely used Robot Operating System (ROS) framework. ARviz aims to provide both a universal visualization platform with the capability of displaying any ROS message data type in AR, as well as a multimodal user interface for interacting with robots over ROS. ARviz is built as a platform incorporating a collection of plugins that provide visualization and/or interaction components. Users can also extend the platform by implementing new plugins to suit their needs. We present three use cases as well as two potential use cases to showcase the capabilities and benefits of the ARviz platform for human-robot interaction applications. The open access source code for our ARviz platform is available at: https://github.com/hri-group/arviz. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2110.15521v1-abstract-full').style.display = 'none'; document.getElementById('2110.15521v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 28 October, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2021. </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, 10 figures, accepted for IEEE RAM - Special Issue on Extended Reality</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2110.03847">arXiv:2110.03847</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2110.03847">pdf</a>, <a href="https://arxiv.org/format/2110.03847">other</a>]&nbsp;</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="Sound">cs.SD</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Audio and Speech Processing">eess.AS</span> </div> </div> <p class="title is-5 mathjax"> Machine Translation Verbosity Control for Automatic Dubbing </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Lakew%2C+S+M">Surafel M. Lakew</a>, <a href="/search/?searchtype=author&amp;query=Federico%2C+M">Marcello Federico</a>, <a href="/search/?searchtype=author&amp;query=Wang%2C+Y">Yue Wang</a>, <a href="/search/?searchtype=author&amp;query=Hoang%2C+C">Cuong Hoang</a>, <a href="/search/?searchtype=author&amp;query=Virkar%2C+Y">Yogesh Virkar</a>, <a href="/search/?searchtype=author&amp;query=Barra-Chicote%2C+R">Roberto Barra-Chicote</a>, <a href="/search/?searchtype=author&amp;query=Enyedi%2C+R">Robert Enyedi</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="2110.03847v1-abstract-short" style="display: inline;"> Automatic dubbing aims at seamlessly replacing the speech in a video document with synthetic speech in a different language. The task implies many challenges, one of which is generating translations that not only convey the original content, but also match the duration of the corresponding utterances. In this paper, we focus on the problem of controlling the verbosity of machine translation output&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2110.03847v1-abstract-full').style.display = 'inline'; document.getElementById('2110.03847v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2110.03847v1-abstract-full" style="display: none;"> Automatic dubbing aims at seamlessly replacing the speech in a video document with synthetic speech in a different language. The task implies many challenges, one of which is generating translations that not only convey the original content, but also match the duration of the corresponding utterances. In this paper, we focus on the problem of controlling the verbosity of machine translation output, so that subsequent steps of our automatic dubbing pipeline can generate dubs of better quality. We propose new methods to control the verbosity of MT output and compare them against the state of the art with both intrinsic and extrinsic evaluations. For our experiments we use a public data set to dub English speeches into French, Italian, German and Spanish. Finally, we report extensive subjective tests that measure the impact of MT verbosity control on the final quality of dubbed video clips. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2110.03847v1-abstract-full').style.display = 'none'; document.getElementById('2110.03847v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 7 October, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2021. </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">Accepted at IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2021</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2107.01008">arXiv:2107.01008</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2107.01008">pdf</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Networking and Internet Architecture">cs.NI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Robotics">cs.RO</span> </div> </div> <p class="title is-5 mathjax"> Developing system of wireless sensor network and unmaned aerial vehicle for agriculture inspection </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Son%2C+N+T">Nguyen Truong Son</a>, <a href="/search/?searchtype=author&amp;query=Hoang%2C+Q+C">Quach Cong Hoang</a>, <a href="/search/?searchtype=author&amp;query=Giang%2C+D+T+H">Dang Thi Huong Giang</a>, <a href="/search/?searchtype=author&amp;query=Trung%2C+V+M">Vu Minh Trung</a>, <a href="/search/?searchtype=author&amp;query=Huy%2C+V+Q">Vuong Quang Huy</a>, <a href="/search/?searchtype=author&amp;query=Tuan%2C+M+A">Mai Anh Tuan</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="2107.01008v1-abstract-short" style="display: inline;"> Agricultural production using high technology is an inevitable trend in Vietnam. Especially for material crops which typically need large growing areas, wireless sensor networks has been clearly playing a significant role in increasing productivity, monitoring pests and diseases, mitigating the impact of climate change, and reducing the direct labor of cultivators. This paper constructs an experim&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2107.01008v1-abstract-full').style.display = 'inline'; document.getElementById('2107.01008v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2107.01008v1-abstract-full" style="display: none;"> Agricultural production using high technology is an inevitable trend in Vietnam. Especially for material crops which typically need large growing areas, wireless sensor networks has been clearly playing a significant role in increasing productivity, monitoring pests and diseases, mitigating the impact of climate change, and reducing the direct labor of cultivators. This paper constructs an experimental model of agricultural crop field monitoring using a combination of LoRa wireless sensor networks and unmanned aerial vehicles to collect data on conditions of weather and soil, plant health, which helps growers easily making right decisions on solutions for irrigation, pest treatment, and fertilization with the currently planted crops. The system has been developed and experimentized in the field to evaluate some basic features and justified the stability and reliability of the obtained data. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2107.01008v1-abstract-full').style.display = 'none'; document.getElementById('2107.01008v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 20 June, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2021. </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">in Vietnamese language. https://tapchikhcn.haui.edu.vn/media/30/uffile-upload-no-title30450.pdf</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Journal of Science &amp; Technology (2020) Volume 56 Issue 9 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2104.05211">arXiv:2104.05211</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2104.05211">pdf</a>, <a href="https://arxiv.org/format/2104.05211">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Robotics">cs.RO</span> </div> </div> <p class="title is-5 mathjax"> Virtual Barriers in Augmented Reality for Safe and Effective Human-Robot Cooperation in Manufacturing </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+K+C">Khoa Cong Hoang</a>, <a href="/search/?searchtype=author&amp;query=Chan%2C+W+P">Wesley P. Chan</a>, <a href="/search/?searchtype=author&amp;query=Lay%2C+S">Steven Lay</a>, <a href="/search/?searchtype=author&amp;query=Cosgun%2C+A">Akansel Cosgun</a>, <a href="/search/?searchtype=author&amp;query=Croft%2C+E">Elizabeth Croft</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="2104.05211v1-abstract-short" style="display: inline;"> Safety is a fundamental requirement in any human-robot collaboration scenario. To ensure the safety of users for such scenarios, we propose a novel Virtual Barrier system facilitated by an augmented reality interface. Our system provides two kinds of Virtual Barriers to ensure safety: 1) a Virtual Person Barrier which encapsulates and follows the user to protect them from colliding with the robot,&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2104.05211v1-abstract-full').style.display = 'inline'; document.getElementById('2104.05211v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2104.05211v1-abstract-full" style="display: none;"> Safety is a fundamental requirement in any human-robot collaboration scenario. To ensure the safety of users for such scenarios, we propose a novel Virtual Barrier system facilitated by an augmented reality interface. Our system provides two kinds of Virtual Barriers to ensure safety: 1) a Virtual Person Barrier which encapsulates and follows the user to protect them from colliding with the robot, and 2) Virtual Obstacle Barriers which users can spawn to protect objects or regions that the robot should not enter. To enable effective human-robot collaboration, our system includes an intuitive robot programming interface utilizing speech commands and hand gestures, and features the capability of automatic path re-planning when potential collisions are detected as a result of a barrier intersecting the robot&#39;s planned path. We compared our novel system with a standard 2D display interface through a user study, where participants performed a task mimicking an industrial manufacturing procedure. Results show that our system increases the user&#39;s sense of safety and task efficiency, and makes the interaction more intuitive. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2104.05211v1-abstract-full').style.display = 'none'; document.getElementById('2104.05211v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 12 April, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> April 2021. </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, submitted to IROS 2021, waiting for result</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2102.03505">arXiv:2102.03505</a> <span>&nbsp;&nbsp;</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> </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/j.cma.2021.114341">10.1016/j.cma.2021.114341 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Projection-based model reduction of dynamical systems using space-time subspace and machine learning </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+C">Chi Hoang</a>, <a href="/search/?searchtype=author&amp;query=Chowdhary%2C+K">Kenny Chowdhary</a>, <a href="/search/?searchtype=author&amp;query=Lee%2C+K">Kookjin Lee</a>, <a href="/search/?searchtype=author&amp;query=Ray%2C+J">Jaideep Ray</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="2102.03505v2-abstract-short" style="display: inline;"> This paper considers the creation of parametric surrogate models for applications in science and engineering where the goal is to predict high-dimensional spatiotemporal output quantities of interest, such as pressure, temperature and displacement fields. The proposed methodology develops a low-dimensional parametrization of these quantities of interest using space-time bases combining with machin&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2102.03505v2-abstract-full').style.display = 'inline'; document.getElementById('2102.03505v2-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2102.03505v2-abstract-full" style="display: none;"> This paper considers the creation of parametric surrogate models for applications in science and engineering where the goal is to predict high-dimensional spatiotemporal output quantities of interest, such as pressure, temperature and displacement fields. The proposed methodology develops a low-dimensional parametrization of these quantities of interest using space-time bases combining with machine learning methods. In particular, the space-time solutions are sought in a low-dimensional space-time linear trial subspace that can be obtained by computing tensor decompositions of usual state-snapshots data. The mapping between the input parameters and the basis expansion coefficients (or generalized coordinates) is approximated using four different machine learning techniques: multivariate polynomial regression, k-nearest-neighbors, random forest and neural network. The relative costs and effectiveness of the four machine learning techniques are explored through three engineering problems: steady heat conduction, unsteady heat conduction and unsteady advective-diffusive-reactive system. Numerical results demonstrate that the proposed method performs well in terms of both accuracy and computational cost, and highlight the important point that the amount of model training data available in an engineering setting is often much less than it is in other machine learning applications, making it essential to incorporate knowledge from physical models. In addition, simpler machine learning techniques are seen to perform better than more elaborate ones. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2102.03505v2-abstract-full').style.display = 'none'; document.getElementById('2102.03505v2-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 22 March, 2022; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 5 February, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2021. </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">Found significant issues with the manuscript</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2007.11835">arXiv:2007.11835</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2007.11835">pdf</a>, <a href="https://arxiv.org/format/2007.11835">other</a>]&nbsp;</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 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/j.cma.2021.113997">10.1016/j.cma.2021.113997 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Domain-decomposition least-squares Petrov-Galerkin (DD-LSPG) nonlinear model reduction </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+C">Chi Hoang</a>, <a href="/search/?searchtype=author&amp;query=Choi%2C+Y">Youngsoo Choi</a>, <a href="/search/?searchtype=author&amp;query=Carlberg%2C+K">Kevin Carlberg</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="2007.11835v2-abstract-short" style="display: inline;"> A novel domain-decomposition least-squares Petrov-Galerkin (DD-LSPG) model-reduction method applicable to parameterized systems of nonlinear algebraic equations (e.g., arising from discretizing a parameterized partial-differential-equations problem) is proposed. In contrast with previous works, we adopt an algebraically non-overlapping decomposition strategy rather than a spatial-decomposition str&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2007.11835v2-abstract-full').style.display = 'inline'; document.getElementById('2007.11835v2-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2007.11835v2-abstract-full" style="display: none;"> A novel domain-decomposition least-squares Petrov-Galerkin (DD-LSPG) model-reduction method applicable to parameterized systems of nonlinear algebraic equations (e.g., arising from discretizing a parameterized partial-differential-equations problem) is proposed. In contrast with previous works, we adopt an algebraically non-overlapping decomposition strategy rather than a spatial-decomposition strategy, which facilitates application to different spatial-discretization schemes. Rather than constructing a low-dimensional subspace for the entire state space in a monolithic fashion, the methodology constructs separate subspaces for the different subdomains/components characterizing the original model. In the offline stage, the method constructs low-dimensional bases for the interior and interface of components. In the online stage, the approach constructs an LSPG ROM for each component and enforces strong or weak compatibility on the &#39;ports&#39; connecting them. We propose four different ways to construct reduced bases on the interface/ports of subdomains and several ways to enforce compatibility across connecting ports. We derive a posteriori and a priori error bounds for the DD-LSPG solutions. Numerical results performed on nonlinear benchmark problems in heat transfer and fluid dynamics demonstrate that the proposed method performs well in terms of both accuracy and computational cost, with different choices of basis and compatibility constraints yielding different performance profiles. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2007.11835v2-abstract-full').style.display = 'none'; document.getElementById('2007.11835v2-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 15 October, 2020; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 23 July, 2020; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2020. </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">43 pages, 17 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/2007.11513">arXiv:2007.11513</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2007.11513">pdf</a>, <a href="https://arxiv.org/format/2007.11513">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Discrete Mathematics">cs.DM</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Combinatorics">math.CO</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/j.disc.2023.113699">10.1016/j.disc.2023.113699 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> A class of graphs with large rankwidth </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Ho%C3%A0ng%2C+C">Ch铆nh Ho脿ng</a>, <a href="/search/?searchtype=author&amp;query=Trotignon%2C+N">Nicolas Trotignon</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="2007.11513v3-abstract-short" style="display: inline;"> We describe several graphs with arbitrarily large rankwidth (or equivalently with arbitrarily large cliquewidth). Korpelainen, Lozin, and Mayhill [Split permutation graphs, Graphs and Combinatorics, 30(3):633-646, 2014] proved that there exist split graphs with Dilworth number 2 with arbitrarily large rankwidth, but without explicitly constructing them. We provide an explicit construction. Maffray&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2007.11513v3-abstract-full').style.display = 'inline'; document.getElementById('2007.11513v3-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2007.11513v3-abstract-full" style="display: none;"> We describe several graphs with arbitrarily large rankwidth (or equivalently with arbitrarily large cliquewidth). Korpelainen, Lozin, and Mayhill [Split permutation graphs, Graphs and Combinatorics, 30(3):633-646, 2014] proved that there exist split graphs with Dilworth number 2 with arbitrarily large rankwidth, but without explicitly constructing them. We provide an explicit construction. Maffray, Penev, and Vu拧kovi膰 [Coloring rings, Journal of Graph Theory 96(4):642-683, 2021] proved that graphs that they call rings on $n$ sets can be colored in polynomial time. We show that for every fixed integer $n\geq 3$, there exist rings on $n$ sets with arbitrarily large rankwidth. When $n\geq 5$ and $n$ is odd, this provides a new construction of even-hole-free graphs with arbitrarily large rankwidth. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2007.11513v3-abstract-full').style.display = 'none'; document.getElementById('2007.11513v3-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 30 August, 2023; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 22 July, 2020; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2020. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">MSC Class:</span> 05C85 <span class="has-text-black-bis has-text-weight-semibold">ACM Class:</span> G.2.2 </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Discrete Mathematics, Volume 347, Issue 1, 2024, 113699 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2007.00057">arXiv:2007.00057</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2007.00057">pdf</a>, <a href="https://arxiv.org/format/2007.00057">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Combinatorics">math.CO</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Discrete Mathematics">cs.DM</span> </div> </div> <p class="title is-5 mathjax"> Dichotomizing $k$-vertex-critical $H$-free graphs for $H$ of order four </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Cameron%2C+B">Ben Cameron</a>, <a href="/search/?searchtype=author&amp;query=Ho%C3%A0ng%2C+C+T">Ch铆nh T. Ho脿ng</a>, <a href="/search/?searchtype=author&amp;query=Sawada%2C+J">Joe Sawada</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="2007.00057v1-abstract-short" style="display: inline;"> For $k \geq 3$, we prove (i) there is a finite number of $k$-vertex-critical $(P_2+\ell P_1)$-free graphs and (ii) $k$-vertex-critical $(P_3+P_1)$-free graphs have at most $2k-1$ vertices. Together with previous research, these results imply the following characterization where $H$ is a graph of order four: There is a finite number of $k$-vertex-critical $H$-free graphs for fixed $k \geq 5$ if and&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2007.00057v1-abstract-full').style.display = 'inline'; document.getElementById('2007.00057v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2007.00057v1-abstract-full" style="display: none;"> For $k \geq 3$, we prove (i) there is a finite number of $k$-vertex-critical $(P_2+\ell P_1)$-free graphs and (ii) $k$-vertex-critical $(P_3+P_1)$-free graphs have at most $2k-1$ vertices. Together with previous research, these results imply the following characterization where $H$ is a graph of order four: There is a finite number of $k$-vertex-critical $H$-free graphs for fixed $k \geq 5$ if and only if $H$ is one of $\overline{K_4}, P_4, P_2 + 2P_1$, or $P_3 + P_1$. Our results imply the existence of new polynomial-time certifying algorithms for deciding the $k$-colorability of $(P_2+\ell P_1)$-free graphs for fixed $k$. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2007.00057v1-abstract-full').style.display = 'none'; document.getElementById('2007.00057v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 30 June, 2020; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2020. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1910.03930">arXiv:1910.03930</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/1910.03930">pdf</a>]&nbsp;</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> </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/j.physe.2019.113638">10.1016/j.physe.2019.113638 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Metastable bound states of the quasi-bimagnetoexcitons in the lowest Landau levels approximation </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Podlesny%2C+I+V">I. V. Podlesny</a>, <a href="/search/?searchtype=author&amp;query=Zubac%2C+I+A">I. A. Zubac</a>, <a href="/search/?searchtype=author&amp;query=Hoang%2C+C+N">Cam Ngoc Hoang</a>, <a href="/search/?searchtype=author&amp;query=Liberman%2C+M+A">M. A. Liberman</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="1910.03930v1-abstract-short" style="display: inline;"> Four different spin structures of two electrons and of two holes situated on the lowest Landau levels (LLLs) are taken into account to investigate possible bound states of the two-dimensional magnetic biexciton formed of two magnetoexcitons with opposite wave vectors and antiparallel dipole moments. The singlet and triplet states of the spins of two electrons and of two holes separately, as well a&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1910.03930v1-abstract-full').style.display = 'inline'; document.getElementById('1910.03930v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1910.03930v1-abstract-full" style="display: none;"> Four different spin structures of two electrons and of two holes situated on the lowest Landau levels (LLLs) are taken into account to investigate possible bound states of the two-dimensional magnetic biexciton formed of two magnetoexcitons with opposite wave vectors and antiparallel dipole moments. The singlet and triplet states of the spins of two electrons and of two holes separately, as well as of two para- and two ortho-magnetoexcitons are considered. The general expressions describing the binding energy of the bound states and the normalization conditions characterized by the effective spin parameter for the corresponding wave functions are derived. The most favorable of the four considered spin configurations happened to be the triplet-triplet spin structure of two electrons and of two holes. In its frame a metastable bound state with activation barrier comparable with two ionization potentials of the magnetoexciton is revealed . <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1910.03930v1-abstract-full').style.display = 'none'; document.getElementById('1910.03930v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 8 October, 2019; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2019. </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">25 pages, 4 figures</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Report number:</span> NORDITA-2019-085 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1904.08180">arXiv:1904.08180</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/1904.08180">pdf</a>, <a href="https://arxiv.org/ps/1904.08180">ps</a>, <a href="https://arxiv.org/format/1904.08180">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Discrete Mathematics">cs.DM</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Combinatorics">math.CO</span> </div> </div> <p class="title is-5 mathjax"> The intersection of two vertex coloring problems </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Foley%2C+A+M">Angele M. Foley</a>, <a href="/search/?searchtype=author&amp;query=Fraser%2C+D+J">Dallas J. Fraser</a>, <a href="/search/?searchtype=author&amp;query=Hoang%2C+C+T">Chinh T. Hoang</a>, <a href="/search/?searchtype=author&amp;query=Holmes%2C+K">Kevin Holmes</a>, <a href="/search/?searchtype=author&amp;query=LaMantia%2C+T+P">Tom P. LaMantia</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="1904.08180v1-abstract-short" style="display: inline;"> A hole is an induced cycle with at least four vertices. A hole is even if its number of vertices is even. Given a set L of graphs, a graph G is L-free if G does not contain any graph in L as an induced subgraph. Currently, the following two problems are unresolved: the complexity of coloring even hole-free graphs, and the complexity of coloring {4K1, C4}-free graphs. The intersection of these two&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1904.08180v1-abstract-full').style.display = 'inline'; document.getElementById('1904.08180v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1904.08180v1-abstract-full" style="display: none;"> A hole is an induced cycle with at least four vertices. A hole is even if its number of vertices is even. Given a set L of graphs, a graph G is L-free if G does not contain any graph in L as an induced subgraph. Currently, the following two problems are unresolved: the complexity of coloring even hole-free graphs, and the complexity of coloring {4K1, C4}-free graphs. The intersection of these two problems is the problem of coloring {4K1, C4, C6}-free graphs. In this paper we present partial results on this problem. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1904.08180v1-abstract-full').style.display = 'none'; document.getElementById('1904.08180v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 17 April, 2019; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> April 2019. </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">16 pages</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">MSC Class:</span> 68R05 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1812.09836">arXiv:1812.09836</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/1812.09836">pdf</a>, <a href="https://arxiv.org/ps/1812.09836">ps</a>, <a href="https://arxiv.org/format/1812.09836">other</a>]&nbsp;</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="Machine Learning">cs.LG</span> </div> </div> <p class="title is-5 mathjax"> Moment Matching Training for Neural Machine Translation: A Preliminary Study </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+C+D+V">Cong Duy Vu Hoang</a>, <a href="/search/?searchtype=author&amp;query=Calapodescu%2C+I">Ioan Calapodescu</a>, <a href="/search/?searchtype=author&amp;query=Dymetman%2C+M">Marc Dymetman</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="1812.09836v2-abstract-short" style="display: inline;"> In previous works, neural sequence models have been shown to improve significantly if external prior knowledge can be provided, for instance by allowing the model to access the embeddings of explicit features during both training and inference. In this work, we propose a different point of view on how to incorporate prior knowledge in a principled way, using a moment matching framework. In this ap&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1812.09836v2-abstract-full').style.display = 'inline'; document.getElementById('1812.09836v2-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1812.09836v2-abstract-full" style="display: none;"> In previous works, neural sequence models have been shown to improve significantly if external prior knowledge can be provided, for instance by allowing the model to access the embeddings of explicit features during both training and inference. In this work, we propose a different point of view on how to incorporate prior knowledge in a principled way, using a moment matching framework. In this approach, the standard local cross-entropy training of the sequential model is combined with a moment matching training mode that encourages the equality of the expectations of certain predefined features between the model distribution and the empirical distribution. In particular, we show how to derive unbiased estimates of some stochastic gradients that are central to the training, and compare our framework with a formally related one: policy gradient training in reinforcement learning, pointing out some important differences in terms of the kinds of prior assumptions in both approaches. Our initial results are promising, showing the effectiveness of our proposed framework. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1812.09836v2-abstract-full').style.display = 'none'; document.getElementById('1812.09836v2-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 27 December, 2018; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 24 December, 2018; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> December 2018. </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">A preliminary study</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1808.03391">arXiv:1808.03391</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/1808.03391">pdf</a>, <a href="https://arxiv.org/ps/1808.03391">ps</a>, <a href="https://arxiv.org/format/1808.03391">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Combinatorics">math.CO</span> </div> </div> <p class="title is-5 mathjax"> Classes of graphs with e-positive chromatic symmetric function </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Foley%2C+A+M">Ang猫le M. Foley</a>, <a href="/search/?searchtype=author&amp;query=Ho%C3%A0ng%2C+C+T">Ch铆nh T. Ho脿ng</a>, <a href="/search/?searchtype=author&amp;query=Merkel%2C+O+D">Owen D. Merkel</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="1808.03391v1-abstract-short" style="display: inline;"> In the mid-1990s, Stanley and Stembridge conjectured that the chromatic symmetric functions of claw-free co-comparability (also called incomparability) graphs were e-positive. The quest for the proof of this conjecture has led to an examination of other, related graph classes. In 2013 Guay-Paquet proved that if unit interval graphs are e-positive, that implies claw-free incomparability graphs are&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1808.03391v1-abstract-full').style.display = 'inline'; document.getElementById('1808.03391v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1808.03391v1-abstract-full" style="display: none;"> In the mid-1990s, Stanley and Stembridge conjectured that the chromatic symmetric functions of claw-free co-comparability (also called incomparability) graphs were e-positive. The quest for the proof of this conjecture has led to an examination of other, related graph classes. In 2013 Guay-Paquet proved that if unit interval graphs are e-positive, that implies claw-free incomparability graphs are as well. Inspired by this approach, we consider a related case and prove that unit interval graphs whose complement is also a unit interval graph are e-positive. We introduce the concept of strongly $e$-positive to denote a graph whose induced subgraphs are all e-positive, and conjecture that a graph is strongly e-positive if and only if it is (claw, net)-free. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1808.03391v1-abstract-full').style.display = 'none'; document.getElementById('1808.03391v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 9 August, 2018; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2018. </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">20 pages</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">MSC Class:</span> 05E05; 05C15 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1709.03354">arXiv:1709.03354</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/1709.03354">pdf</a>, <a href="https://arxiv.org/ps/1709.03354">ps</a>, <a href="https://arxiv.org/format/1709.03354">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Combinatorics">math.CO</span> </div> </div> <p class="title is-5 mathjax"> Chromatic symmetric functions and H-free graphs </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hamel%2C+A+M">Ang猫le M. Hamel</a>, <a href="/search/?searchtype=author&amp;query=Ho%C3%A0ng%2C+C+T">Ch铆nh T. Ho脿ng</a>, <a href="/search/?searchtype=author&amp;query=Tuero%2C+J+E">Jake E. Tuero</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="1709.03354v1-abstract-short" style="display: inline;"> Two celebrated conjectures in chromatic symmetric function theory concern the positivity chromatics symmetric functions of claw-free graphs. Here we extend the claw-free idea to general graphs and consider the e-positivity question for H-free graphs where H = {claw, F} and H={claw, F, co-F}, where F is a four-vertex graph. We settle the question for all cases except H={claw, co-diamond}, and we pr&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1709.03354v1-abstract-full').style.display = 'inline'; document.getElementById('1709.03354v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1709.03354v1-abstract-full" style="display: none;"> Two celebrated conjectures in chromatic symmetric function theory concern the positivity chromatics symmetric functions of claw-free graphs. Here we extend the claw-free idea to general graphs and consider the e-positivity question for H-free graphs where H = {claw, F} and H={claw, F, co-F}, where F is a four-vertex graph. We settle the question for all cases except H={claw, co-diamond}, and we provide some partial results in that case. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1709.03354v1-abstract-full').style.display = 'none'; document.getElementById('1709.03354v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 11 September, 2017; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> September 2017. </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</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">MSC Class:</span> 05E05; 05C15 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1704.00316">arXiv:1704.00316</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/1704.00316">pdf</a>, <a href="https://arxiv.org/ps/1704.00316">ps</a>, <a href="https://arxiv.org/format/1704.00316">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Discrete Mathematics">cs.DM</span> </div> </div> <p class="title is-5 mathjax"> Solving the clique cover problem on (bull, $C_4$)-free graphs </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Cameron%2C+K">Kathie Cameron</a>, <a href="/search/?searchtype=author&amp;query=Ho%C3%A0ng%2C+C+T">Ch铆nh T. Ho脿ng</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="1704.00316v1-abstract-short" style="display: inline;"> We give an $O(n^4)$ algorithm to find a minimum clique cover of a (bull, $C_4$)-free graph, or equivalently, a minimum colouring of a (bull, $2K_2$)-free graph, where $n$ is the number of vertices of the graphs. </span> <span class="abstract-full has-text-grey-dark mathjax" id="1704.00316v1-abstract-full" style="display: none;"> We give an $O(n^4)$ algorithm to find a minimum clique cover of a (bull, $C_4$)-free graph, or equivalently, a minimum colouring of a (bull, $2K_2$)-free graph, where $n$ is the number of vertices of the graphs. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1704.00316v1-abstract-full').style.display = 'none'; document.getElementById('1704.00316v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 2 April, 2017; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> April 2017. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">MSC Class:</span> 05C15 <span class="has-text-black-bis has-text-weight-semibold">ACM Class:</span> G.2.1 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1703.07901">arXiv:1703.07901</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/1703.07901">pdf</a>, <a href="https://arxiv.org/format/1703.07901">other</a>]&nbsp;</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 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/10.3390/axioms6030021">10.3390/axioms6030021 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> The SIC Question: History and State of Play </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Fuchs%2C+C+A">Christopher A. Fuchs</a>, <a href="/search/?searchtype=author&amp;query=Hoang%2C+M+C">Michael C. Hoang</a>, <a href="/search/?searchtype=author&amp;query=Stacey%2C+B+C">Blake C. Stacey</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="1703.07901v3-abstract-short" style="display: inline;"> Recent years have seen significant advances in the study of symmetric informationally complete (SIC) quantum measurements, also known as maximal sets of complex equiangular lines. Previously, the published record contained solutions up to dimension 67, and was with high confidence complete up through dimension 50. Computer calculations have now furnished solutions in all dimensions up to 151, and&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1703.07901v3-abstract-full').style.display = 'inline'; document.getElementById('1703.07901v3-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1703.07901v3-abstract-full" style="display: none;"> Recent years have seen significant advances in the study of symmetric informationally complete (SIC) quantum measurements, also known as maximal sets of complex equiangular lines. Previously, the published record contained solutions up to dimension 67, and was with high confidence complete up through dimension 50. Computer calculations have now furnished solutions in all dimensions up to 151, and in several cases beyond that, as large as dimension 844. These new solutions exhibit an additional type of symmetry beyond the basic definition of a SIC, and so verify a conjecture of Zauner in many new cases. The solutions in dimensions 68 through 121 were obtained by Andrew Scott, and his catalogue of distinct solutions is, with high confidence, complete up to dimension 90. Additional results in dimensions 122 through 151 were calculated by the authors using Scott&#39;s code. We recap the history of the problem, outline how the numerical searches were done, and pose some conjectures on how the search technique could be improved. In order to facilitate communication across disciplinary boundaries, we also present a comprehensive bibliography of SIC research. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1703.07901v3-abstract-full').style.display = 'none'; document.getElementById('1703.07901v3-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 11 July, 2017; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 22 March, 2017; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2017. </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">16 pages, 1 figure, many references; v3: updating bibliography, dimension eight hundred forty four</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Axioms 2017, 6(3), 21 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1701.02854">arXiv:1701.02854</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/1701.02854">pdf</a>, <a href="https://arxiv.org/format/1701.02854">other</a>]&nbsp;</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"> Towards Decoding as Continuous Optimization in Neural Machine Translation </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+C+D+V">Cong Duy Vu Hoang</a>, <a href="/search/?searchtype=author&amp;query=Haffari%2C+G">Gholamreza Haffari</a>, <a href="/search/?searchtype=author&amp;query=Cohn%2C+T">Trevor Cohn</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="1701.02854v4-abstract-short" style="display: inline;"> We propose a novel decoding approach for neural machine translation (NMT) based on continuous optimisation. We convert decoding - basically a discrete optimization problem - into a continuous optimization problem. The resulting constrained continuous optimisation problem is then tackled using gradient-based methods. Our powerful decoding framework enables decoding intractable models such as the in&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1701.02854v4-abstract-full').style.display = 'inline'; document.getElementById('1701.02854v4-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1701.02854v4-abstract-full" style="display: none;"> We propose a novel decoding approach for neural machine translation (NMT) based on continuous optimisation. We convert decoding - basically a discrete optimization problem - into a continuous optimization problem. The resulting constrained continuous optimisation problem is then tackled using gradient-based methods. Our powerful decoding framework enables decoding intractable models such as the intersection of left-to-right and right-to-left (bidirectional) as well as source-to-target and target-to-source (bilingual) NMT models. Our empirical results show that our decoding framework is effective, and leads to substantial improvements in translations generated from the intersected models where the typical greedy or beam search is not feasible. We also compare our framework against reranking, and analyse its advantages and disadvantages. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1701.02854v4-abstract-full').style.display = 'none'; document.getElementById('1701.02854v4-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 22 July, 2017; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 11 January, 2017; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 2017. </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">EMNLP 2017 Camera Ready Paper</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1609.03889">arXiv:1609.03889</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/1609.03889">pdf</a>, <a href="https://arxiv.org/ps/1609.03889">ps</a>, <a href="https://arxiv.org/format/1609.03889">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Classical Analysis and ODEs">math.CA</span> </div> </div> <p class="title is-5 mathjax"> Muckenhoupt-Wheeden conjectures for sparse operators </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+C">Cong Hoang</a>, <a href="/search/?searchtype=author&amp;query=Moen%2C+K">Kabe Moen</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="1609.03889v2-abstract-short" style="display: inline;"> We provide an example of a pair of weights $(u,v)$ for which the Hardy-Littlewood maximal function is bounded from $L^p(v)$ to $L^p(u)$ and from $L^{p&#39;}(u^{1-p&#39;})$ to $L^{p&#39;}(v^{1-p&#39;})$ while a dyadic sparse operator is not bounded on the same domain and range. Our construction also provides an example of a single weight for which the weak-type endpoint does not hold for sparse operators. </span> <span class="abstract-full has-text-grey-dark mathjax" id="1609.03889v2-abstract-full" style="display: none;"> We provide an example of a pair of weights $(u,v)$ for which the Hardy-Littlewood maximal function is bounded from $L^p(v)$ to $L^p(u)$ and from $L^{p&#39;}(u^{1-p&#39;})$ to $L^{p&#39;}(v^{1-p&#39;})$ while a dyadic sparse operator is not bounded on the same domain and range. Our construction also provides an example of a single weight for which the weak-type endpoint does not hold for sparse operators. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1609.03889v2-abstract-full').style.display = 'none'; document.getElementById('1609.03889v2-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 11 January, 2017; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 13 September, 2016; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> September 2016. </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">An updated version as suggested by the referee</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1601.07590">arXiv:1601.07590</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/1601.07590">pdf</a>, <a href="https://arxiv.org/ps/1601.07590">ps</a>, <a href="https://arxiv.org/format/1601.07590">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Classical Analysis and ODEs">math.CA</span> </div> </div> <p class="title is-5 mathjax"> Weighted estimates for bilinear fractional integral operators and their commutators </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Hoang%2C+C">Cong Hoang</a>, <a href="/search/?searchtype=author&amp;query=Moen%2C+K">Kabe Moen</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="1601.07590v1-abstract-short" style="display: inline;"> In this paper we prove several weighted estimates for bilinear fractional integral operators and their commutators with BMO functions. We also prove maximal function control theorem for these operators, that is, we prove the weighted $L^p$ norm is bounded by the weighted $L^p$ norm of a natural maximal operator when the weight belongs to $A_\infty$. As a corollary we are able to obtain new weighte&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1601.07590v1-abstract-full').style.display = 'inline'; document.getElementById('1601.07590v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1601.07590v1-abstract-full" style="display: none;"> In this paper we prove several weighted estimates for bilinear fractional integral operators and their commutators with BMO functions. We also prove maximal function control theorem for these operators, that is, we prove the weighted $L^p$ norm is bounded by the weighted $L^p$ norm of a natural maximal operator when the weight belongs to $A_\infty$. As a corollary we are able to obtain new weighted estimates for the bilinear maximal function associated to the bilinear Hilbert transform. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1601.07590v1-abstract-full').style.display = 'none'; document.getElementById('1601.07590v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 27 January, 2016; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 2016. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1601.01085">arXiv:1601.01085</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/1601.01085">pdf</a>, <a href="https://arxiv.org/format/1601.01085">other</a>]&nbsp;</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 Structural Alignment Biases into an Attentional Neural Translation Model </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&amp;query=Cohn%2C+T">Trevor Cohn</a>, <a href="/search/?searchtype=author&amp;query=Hoang%2C+C+D+V">Cong Duy Vu Hoang</a>, <a href="/search/?searchtype=author&amp;query=Vymolova%2C+E">Ekaterina Vymolova</a>, <a href="/search/?searchtype=author&amp;query=Yao%2C+K">Kaisheng Yao</a>, <a href="/search/?searchtype=author&amp;query=Dyer%2C+C">Chris Dyer</a>, <a href="/search/?searchtype=author&amp;query=Haffari%2C+G">Gholamreza Haffari</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="1601.01085v1-abstract-short" style="display: inline;"> Neural encoder-decoder models of machine translation have achieved impressive results, rivalling traditional translation models. However their modelling formulation is overly simplistic, and omits several key inductive biases built into traditional models. In this paper we extend the attentional neural translation model to include structural biases from word based alignment models, including posit&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1601.01085v1-abstract-full').style.display = 'inline'; document.getElementById('1601.01085v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1601.01085v1-abstract-full" style="display: none;"> Neural encoder-decoder models of machine translation have achieved impressive results, rivalling traditional translation models. However their modelling formulation is overly simplistic, and omits several key inductive biases built into traditional models. In this paper we extend the attentional neural translation model to include structural biases from word based alignment models, including positional bias, Markov conditioning, fertility and agreement over translation directions. We show improvements over a baseline attentional model and standard phrase-based model over several language pairs, evaluating on difficult languages in a low resource setting. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1601.01085v1-abstract-full').style.display = 'none'; document.getElementById('1601.01085v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 6 January, 2016; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 2016. </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</span> </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 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