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class="control is-expanded"> <label for="query" class="hidden-label">Search term or terms</label> <input class="input is-medium" id="query" name="query" placeholder="Search term..." type="text" value="Walker, L"> </div> <div class="select control is-medium"> <label class="is-hidden" for="searchtype">Field</label> <select class="is-medium" id="searchtype" name="searchtype"><option value="all">All fields</option><option value="title">Title</option><option selected value="author">Author(s)</option><option value="abstract">Abstract</option><option value="comments">Comments</option><option value="journal_ref">Journal reference</option><option value="acm_class">ACM classification</option><option value="msc_class">MSC classification</option><option value="report_num">Report number</option><option value="paper_id">arXiv identifier</option><option value="doi">DOI</option><option value="orcid">ORCID</option><option value="license">License (URI)</option><option value="author_id">arXiv author 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name="searchtype"><option value="all">All fields</option><option value="title">Title</option><option selected value="author">Author(s)</option><option value="abstract">Abstract</option><option value="comments">Comments</option><option value="journal_ref">Journal reference</option><option value="acm_class">ACM classification</option><option value="msc_class">MSC classification</option><option value="report_num">Report number</option><option value="paper_id">arXiv identifier</option><option value="doi">DOI</option><option value="orcid">ORCID</option><option value="license">License (URI)</option><option value="author_id">arXiv author ID</option><option value="help">Help pages</option><option value="full_text">Full text</option></select> <input id="query" name="query" type="text" value="Walker, L"> <ul id="abstracts"><li><input checked id="abstracts-0" name="abstracts" type="radio" value="show"> <label for="abstracts-0">Show abstracts</label></li><li><input id="abstracts-1" name="abstracts" type="radio" value="hide"> <label for="abstracts-1">Hide abstracts</label></li></ul> </div> <div class="box field is-grouped is-grouped-multiline level-item"> <div class="control"> <span class="select is-small"> <select id="size" name="size"><option value="25">25</option><option selected value="50">50</option><option value="100">100</option><option value="200">200</option></select> </span> <label for="size">results per page</label>. </div> <div class="control"> <label for="order">Sort results by</label> <span class="select is-small"> <select id="order" name="order"><option selected value="-announced_date_first">Announcement date (newest first)</option><option value="announced_date_first">Announcement date (oldest first)</option><option value="-submitted_date">Submission date (newest first)</option><option value="submitted_date">Submission date (oldest first)</option><option value="">Relevance</option></select> </span> </div> <div class="control"> <button class="button is-small is-link">Go</button> </div> </div> </form> </div> </div> <ol class="breathe-horizontal" start="1"> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.14425">arXiv:2411.14425</a> <span> [<a href="https://arxiv.org/pdf/2411.14425">pdf</a>, <a href="https://arxiv.org/format/2411.14425">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computers and Society">cs.CY</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"> Whack-a-Chip: The Futility of Hardware-Centric Export Controls </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Gupta%2C+R">Ritwik Gupta</a>, <a href="/search/cs?searchtype=author&query=Walker%2C+L">Leah Walker</a>, <a href="/search/cs?searchtype=author&query=Reddie%2C+A+W">Andrew W. Reddie</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="2411.14425v1-abstract-short" style="display: inline;"> U.S. export controls on semiconductors are widely known to be permeable, with the People's Republic of China (PRC) steadily creating state-of-the-art artificial intelligence (AI) models with exfiltrated chips. This paper presents the first concrete, public evidence of how leading PRC AI labs evade and circumvent U.S. export controls. We examine how Chinese companies, notably Tencent, are not only… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.14425v1-abstract-full').style.display = 'inline'; document.getElementById('2411.14425v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.14425v1-abstract-full" style="display: none;"> U.S. export controls on semiconductors are widely known to be permeable, with the People's Republic of China (PRC) steadily creating state-of-the-art artificial intelligence (AI) models with exfiltrated chips. This paper presents the first concrete, public evidence of how leading PRC AI labs evade and circumvent U.S. export controls. We examine how Chinese companies, notably Tencent, are not only using chips that are restricted under U.S. export controls but are also finding ways to circumvent these regulations by using software and modeling techniques that maximize less capable hardware. Specifically, we argue that Tencent's ability to power its Hunyuan-Large model with non-export controlled NVIDIA H20s exemplifies broader gains in efficiency in machine learning that have eroded the moat that the United States initially built via its existing export controls. Finally, we examine the implications of this finding for the future of the United States' export control strategy. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.14425v1-abstract-full').style.display = 'none'; document.getElementById('2411.14425v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 21 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2409.17216">arXiv:2409.17216</a> <span> [<a href="https://arxiv.org/pdf/2409.17216">pdf</a>, <a href="https://arxiv.org/format/2409.17216">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computers and Society">cs.CY</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"> Data-Centric AI Governance: Addressing the Limitations of Model-Focused Policies </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Gupta%2C+R">Ritwik Gupta</a>, <a href="/search/cs?searchtype=author&query=Walker%2C+L">Leah Walker</a>, <a href="/search/cs?searchtype=author&query=Corona%2C+R">Rodolfo Corona</a>, <a href="/search/cs?searchtype=author&query=Fu%2C+S">Stephanie Fu</a>, <a href="/search/cs?searchtype=author&query=Petryk%2C+S">Suzanne Petryk</a>, <a href="/search/cs?searchtype=author&query=Napolitano%2C+J">Janet Napolitano</a>, <a href="/search/cs?searchtype=author&query=Darrell%2C+T">Trevor Darrell</a>, <a href="/search/cs?searchtype=author&query=Reddie%2C+A+W">Andrew W. Reddie</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="2409.17216v1-abstract-short" style="display: inline;"> Current regulations on powerful AI capabilities are narrowly focused on "foundation" or "frontier" models. However, these terms are vague and inconsistently defined, leading to an unstable foundation for governance efforts. Critically, policy debates often fail to consider the data used with these models, despite the clear link between data and model performance. Even (relatively) "small" models t… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2409.17216v1-abstract-full').style.display = 'inline'; document.getElementById('2409.17216v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2409.17216v1-abstract-full" style="display: none;"> Current regulations on powerful AI capabilities are narrowly focused on "foundation" or "frontier" models. However, these terms are vague and inconsistently defined, leading to an unstable foundation for governance efforts. Critically, policy debates often fail to consider the data used with these models, despite the clear link between data and model performance. Even (relatively) "small" models that fall outside the typical definitions of foundation and frontier models can achieve equivalent outcomes when exposed to sufficiently specific datasets. In this work, we illustrate the importance of considering dataset size and content as essential factors in assessing the risks posed by models both today and in the future. More broadly, we emphasize the risk posed by over-regulating reactively and provide a path towards careful, quantitative evaluation of capabilities that can lead to a simplified regulatory environment. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2409.17216v1-abstract-full').style.display = 'none'; document.getElementById('2409.17216v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 25 September, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> September 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2405.12167">arXiv:2405.12167</a> <span> [<a href="https://arxiv.org/pdf/2405.12167">pdf</a>, <a href="https://arxiv.org/format/2405.12167">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computers and Society">cs.CY</span> </div> </div> <p class="title is-5 mathjax"> Open-Source Assessments of AI Capabilities: The Proliferation of AI Analysis Tools, Replicating Competitor Models, and the Zhousidun Dataset </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Gupta%2C+R">Ritwik Gupta</a>, <a href="/search/cs?searchtype=author&query=Walker%2C+L">Leah Walker</a>, <a href="/search/cs?searchtype=author&query=Glickman%2C+E">Eli Glickman</a>, <a href="/search/cs?searchtype=author&query=Koizumi%2C+R">Raine Koizumi</a>, <a href="/search/cs?searchtype=author&query=Bhatnagar%2C+S">Sarthak Bhatnagar</a>, <a href="/search/cs?searchtype=author&query=Reddie%2C+A+W">Andrew W. Reddie</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="2405.12167v3-abstract-short" style="display: inline;"> The integration of artificial intelligence (AI) into military capabilities has become a norm for major military power across the globe. Understanding how these AI models operate is essential for maintaining strategic advantages and ensuring security. This paper demonstrates an open-source methodology for analyzing military AI models through a detailed examination of the Zhousidun dataset, a Chines… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2405.12167v3-abstract-full').style.display = 'inline'; document.getElementById('2405.12167v3-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2405.12167v3-abstract-full" style="display: none;"> The integration of artificial intelligence (AI) into military capabilities has become a norm for major military power across the globe. Understanding how these AI models operate is essential for maintaining strategic advantages and ensuring security. This paper demonstrates an open-source methodology for analyzing military AI models through a detailed examination of the Zhousidun dataset, a Chinese-originated dataset that exhaustively labels critical components on American and Allied destroyers. By demonstrating the replication of a state-of-the-art computer vision model on this dataset, we illustrate how open-source tools can be leveraged to assess and understand key military AI capabilities. This methodology offers a robust framework for evaluating the performance and potential of AI-enabled military capabilities, thus enhancing the accuracy and reliability of strategic assessments. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2405.12167v3-abstract-full').style.display = 'none'; document.getElementById('2405.12167v3-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 24 May, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 20 May, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> May 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2405.01925">arXiv:2405.01925</a> <span> [<a href="https://arxiv.org/pdf/2405.01925">pdf</a>, <a href="https://arxiv.org/format/2405.01925">other</a>] </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 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/10.1109/ICRA57147.2024.10611527">10.1109/ICRA57147.2024.10611527 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> A Modular, Tendon Driven Variable Stiffness Manipulator with Internal Routing for Improved Stability and Increased Payload Capacity </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Walker%2C+K+L">Kyle L. Walker</a>, <a href="/search/cs?searchtype=author&query=Partridge%2C+A+J">Alix J. Partridge</a>, <a href="/search/cs?searchtype=author&query=Chen%2C+H">Hsing-Yu Chen</a>, <a href="/search/cs?searchtype=author&query=Ramachandran%2C+R+R">Rahul R. Ramachandran</a>, <a href="/search/cs?searchtype=author&query=Stokes%2C+A+A">Adam A. Stokes</a>, <a href="/search/cs?searchtype=author&query=Tadakuma%2C+K">Kenjiro Tadakuma</a>, <a href="/search/cs?searchtype=author&query=da+Silva%2C+L+C">Lucas Cruz da Silva</a>, <a href="/search/cs?searchtype=author&query=Giorgio-Serchi%2C+F">Francesco Giorgio-Serchi</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="2405.01925v1-abstract-short" style="display: inline;"> Stability and reliable operation under a spectrum of environmental conditions is still an open challenge for soft and continuum style manipulators. The inability to carry sufficient load and effectively reject external disturbances are two drawbacks which limit the scale of continuum designs, preventing widespread adoption of this technology. To tackle these problems, this work details the design… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2405.01925v1-abstract-full').style.display = 'inline'; document.getElementById('2405.01925v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2405.01925v1-abstract-full" style="display: none;"> Stability and reliable operation under a spectrum of environmental conditions is still an open challenge for soft and continuum style manipulators. The inability to carry sufficient load and effectively reject external disturbances are two drawbacks which limit the scale of continuum designs, preventing widespread adoption of this technology. To tackle these problems, this work details the design and experimental testing of a modular, tendon driven bead-style continuum manipulator with tunable stiffness. By embedding the ability to independently control the stiffness of distinct sections of the structure, the manipulator can regulate it's posture under greater loads of up to 1kg at the end-effector, with reference to the flexible state. Likewise, an internal routing scheme vastly improves the stability of the proximal segment when operating the distal segment, reducing deviations by at least 70.11%. Operation is validated when gravity is both tangential and perpendicular to the manipulator backbone, a feature uncommon in previous designs. The findings presented in this work are key to the development of larger scale continuum designs, demonstrating that flexibility and tip stability under loading can co-exist without compromise. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2405.01925v1-abstract-full').style.display = 'none'; document.getElementById('2405.01925v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 3 May, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> May 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">To be presented at ICRA 2024, Yokohama, Japan. 6 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/2403.05530">arXiv:2403.05530</a> <span> [<a href="https://arxiv.org/pdf/2403.05530">pdf</a>, <a href="https://arxiv.org/format/2403.05530">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> </div> </div> <p class="title is-5 mathjax"> Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Gemini+Team"> Gemini Team</a>, <a href="/search/cs?searchtype=author&query=Georgiev%2C+P">Petko Georgiev</a>, <a href="/search/cs?searchtype=author&query=Lei%2C+V+I">Ving Ian Lei</a>, <a href="/search/cs?searchtype=author&query=Burnell%2C+R">Ryan Burnell</a>, <a href="/search/cs?searchtype=author&query=Bai%2C+L">Libin Bai</a>, <a href="/search/cs?searchtype=author&query=Gulati%2C+A">Anmol Gulati</a>, <a href="/search/cs?searchtype=author&query=Tanzer%2C+G">Garrett Tanzer</a>, <a href="/search/cs?searchtype=author&query=Vincent%2C+D">Damien Vincent</a>, <a href="/search/cs?searchtype=author&query=Pan%2C+Z">Zhufeng Pan</a>, <a href="/search/cs?searchtype=author&query=Wang%2C+S">Shibo Wang</a>, <a href="/search/cs?searchtype=author&query=Mariooryad%2C+S">Soroosh Mariooryad</a>, <a href="/search/cs?searchtype=author&query=Ding%2C+Y">Yifan Ding</a>, <a href="/search/cs?searchtype=author&query=Geng%2C+X">Xinyang Geng</a>, <a href="/search/cs?searchtype=author&query=Alcober%2C+F">Fred Alcober</a>, <a href="/search/cs?searchtype=author&query=Frostig%2C+R">Roy Frostig</a>, <a href="/search/cs?searchtype=author&query=Omernick%2C+M">Mark Omernick</a>, <a href="/search/cs?searchtype=author&query=Walker%2C+L">Lexi Walker</a>, <a href="/search/cs?searchtype=author&query=Paduraru%2C+C">Cosmin Paduraru</a>, <a href="/search/cs?searchtype=author&query=Sorokin%2C+C">Christina Sorokin</a>, <a href="/search/cs?searchtype=author&query=Tacchetti%2C+A">Andrea Tacchetti</a>, <a href="/search/cs?searchtype=author&query=Gaffney%2C+C">Colin Gaffney</a>, <a href="/search/cs?searchtype=author&query=Daruki%2C+S">Samira Daruki</a>, <a href="/search/cs?searchtype=author&query=Sercinoglu%2C+O">Olcan Sercinoglu</a>, <a href="/search/cs?searchtype=author&query=Gleicher%2C+Z">Zach Gleicher</a>, <a href="/search/cs?searchtype=author&query=Love%2C+J">Juliette Love</a> , et al. (1112 additional authors not shown) </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2403.05530v5-abstract-short" style="display: inline;"> In this report, we introduce the Gemini 1.5 family of models, representing the next generation of highly compute-efficient multimodal models capable of recalling and reasoning over fine-grained information from millions of tokens of context, including multiple long documents and hours of video and audio. The family includes two new models: (1) an updated Gemini 1.5 Pro, which exceeds the February… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2403.05530v5-abstract-full').style.display = 'inline'; document.getElementById('2403.05530v5-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2403.05530v5-abstract-full" style="display: none;"> In this report, we introduce the Gemini 1.5 family of models, representing the next generation of highly compute-efficient multimodal models capable of recalling and reasoning over fine-grained information from millions of tokens of context, including multiple long documents and hours of video and audio. The family includes two new models: (1) an updated Gemini 1.5 Pro, which exceeds the February version on the great majority of capabilities and benchmarks; (2) Gemini 1.5 Flash, a more lightweight variant designed for efficiency with minimal regression in quality. Gemini 1.5 models achieve near-perfect recall on long-context retrieval tasks across modalities, improve the state-of-the-art in long-document QA, long-video QA and long-context ASR, and match or surpass Gemini 1.0 Ultra's state-of-the-art performance across a broad set of benchmarks. Studying the limits of Gemini 1.5's long-context ability, we find continued improvement in next-token prediction and near-perfect retrieval (>99%) up to at least 10M tokens, a generational leap over existing models such as Claude 3.0 (200k) and GPT-4 Turbo (128k). Finally, we highlight real-world use cases, such as Gemini 1.5 collaborating with professionals on completing their tasks achieving 26 to 75% time savings across 10 different job categories, as well as surprising new capabilities of large language models at the frontier; when given a grammar manual for Kalamang, a language with fewer than 200 speakers worldwide, the model learns to translate English to Kalamang at a similar level to a person who learned from the same content. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2403.05530v5-abstract-full').style.display = 'none'; document.getElementById('2403.05530v5-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 16 December, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 8 March, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2401.15886">arXiv:2401.15886</a> <span> [<a href="https://arxiv.org/pdf/2401.15886">pdf</a>, <a href="https://arxiv.org/format/2401.15886">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> </div> <div 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/10.1007/978-981-97-1335-6_7">10.1007/978-981-97-1335-6_7 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Grey Level Texture Features for Segmentation of Chromogenic Dye RNAscope From Breast Cancer Tissue </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Davidson%2C+A">Andrew Davidson</a>, <a href="/search/cs?searchtype=author&query=Morley-Bunker%2C+A">Arthur Morley-Bunker</a>, <a href="/search/cs?searchtype=author&query=Wiggins%2C+G">George Wiggins</a>, <a href="/search/cs?searchtype=author&query=Walker%2C+L">Logan Walker</a>, <a href="/search/cs?searchtype=author&query=Harris%2C+G">Gavin Harris</a>, <a href="/search/cs?searchtype=author&query=Mukundan%2C+R">Ramakrishnan Mukundan</a>, <a href="/search/cs?searchtype=author&query=Investigators%2C+k">kConFab Investigators</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="2401.15886v2-abstract-short" style="display: inline;"> Chromogenic RNAscope dye and haematoxylin staining of cancer tissue facilitates diagnosis of the cancer type and subsequent treatment, and fits well into existing pathology workflows. However, manual quantification of the RNAscope transcripts (dots), which signify gene expression, is prohibitively time consuming. In addition, there is a lack of verified supporting methods for quantification and an… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2401.15886v2-abstract-full').style.display = 'inline'; document.getElementById('2401.15886v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2401.15886v2-abstract-full" style="display: none;"> Chromogenic RNAscope dye and haematoxylin staining of cancer tissue facilitates diagnosis of the cancer type and subsequent treatment, and fits well into existing pathology workflows. However, manual quantification of the RNAscope transcripts (dots), which signify gene expression, is prohibitively time consuming. In addition, there is a lack of verified supporting methods for quantification and analysis. This paper investigates the usefulness of grey level texture features for automatically segmenting and classifying the positions of RNAscope transcripts from breast cancer tissue. Feature analysis showed that a small set of grey level features, including Grey Level Dependence Matrix and Neighbouring Grey Tone Difference Matrix features, were well suited for the task. The automated method performed similarly to expert annotators at identifying the positions of RNAscope transcripts, with an F1-score of 0.571 compared to the expert inter-rater F1-score of 0.596. These results demonstrate the potential of grey level texture features for automated quantification of RNAscope in the pathology workflow. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2401.15886v2-abstract-full').style.display = 'none'; document.getElementById('2401.15886v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 12 March, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 28 January, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 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">This preprint has not undergone peer review (when applicable) or any post-submission improvements or corrections. The Version of Record of this contribution is published in Proceedings of 2023 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2023), and is available online at https://doi.org/10.1007/978-981-97-1335-6_7</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2401.13439">arXiv:2401.13439</a> <span> [<a href="https://arxiv.org/pdf/2401.13439">pdf</a>, <a href="https://arxiv.org/format/2401.13439">other</a>] </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="Systems and Control">eess.SY</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/10.1109/RoboSoft60065.2024.10521974">10.1109/RoboSoft60065.2024.10521974 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Model Predictive Wave Disturbance Rejection for Underwater Soft Robotic Manipulators </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Walker%2C+K+L">Kyle L. Walker</a>, <a href="/search/cs?searchtype=author&query=Della+Santina%2C+C">Cosimo Della Santina</a>, <a href="/search/cs?searchtype=author&query=Giorgio-Serchi%2C+F">Francesco Giorgio-Serchi</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="2401.13439v1-abstract-short" style="display: inline;"> Inspired by the octopus and other animals living in water, soft robots should naturally lend themselves to underwater operations, as supported by encouraging validations in deep water scenarios. This work deals with equipping soft arms with the intelligence necessary to move precisely in wave-dominated environments, such as shallow waters where marine renewable devices are located. This scenario i… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2401.13439v1-abstract-full').style.display = 'inline'; document.getElementById('2401.13439v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2401.13439v1-abstract-full" style="display: none;"> Inspired by the octopus and other animals living in water, soft robots should naturally lend themselves to underwater operations, as supported by encouraging validations in deep water scenarios. This work deals with equipping soft arms with the intelligence necessary to move precisely in wave-dominated environments, such as shallow waters where marine renewable devices are located. This scenario is substantially more challenging than calm deep water since, at low operational depths, hydrodynamic wave disturbances can represent a significant impediment. We propose a control strategy based on Nonlinear Model Predictive Control that can account for wave disturbances explicitly, optimising control actions by considering an estimate of oncoming hydrodynamic loads. The proposed strategy is validated through a set of tasks covering set-point regulation, trajectory tracking and mechanical failure compensation, all under a broad range of varying significant wave heights and peak spectral periods. The proposed control methodology displays positional error reductions as large as 84% with respect to a baseline controller, proving the effectiveness of the method. These initial findings present a first step in the development and deployment of soft manipulators for performing tasks in hazardous water environments. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2401.13439v1-abstract-full').style.display = 'none'; document.getElementById('2401.13439v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 24 January, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 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">To be presented at RoboSoft 2024, San Diego</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2312.11805">arXiv:2312.11805</a> <span> [<a href="https://arxiv.org/pdf/2312.11805">pdf</a>, <a href="https://arxiv.org/format/2312.11805">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> </div> </div> <p class="title is-5 mathjax"> Gemini: A Family of Highly Capable Multimodal Models </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Gemini+Team"> Gemini Team</a>, <a href="/search/cs?searchtype=author&query=Anil%2C+R">Rohan Anil</a>, <a href="/search/cs?searchtype=author&query=Borgeaud%2C+S">Sebastian Borgeaud</a>, <a href="/search/cs?searchtype=author&query=Alayrac%2C+J">Jean-Baptiste Alayrac</a>, <a href="/search/cs?searchtype=author&query=Yu%2C+J">Jiahui Yu</a>, <a href="/search/cs?searchtype=author&query=Soricut%2C+R">Radu Soricut</a>, <a href="/search/cs?searchtype=author&query=Schalkwyk%2C+J">Johan Schalkwyk</a>, <a href="/search/cs?searchtype=author&query=Dai%2C+A+M">Andrew M. Dai</a>, <a href="/search/cs?searchtype=author&query=Hauth%2C+A">Anja Hauth</a>, <a href="/search/cs?searchtype=author&query=Millican%2C+K">Katie Millican</a>, <a href="/search/cs?searchtype=author&query=Silver%2C+D">David Silver</a>, <a href="/search/cs?searchtype=author&query=Johnson%2C+M">Melvin Johnson</a>, <a href="/search/cs?searchtype=author&query=Antonoglou%2C+I">Ioannis Antonoglou</a>, <a href="/search/cs?searchtype=author&query=Schrittwieser%2C+J">Julian Schrittwieser</a>, <a href="/search/cs?searchtype=author&query=Glaese%2C+A">Amelia Glaese</a>, <a href="/search/cs?searchtype=author&query=Chen%2C+J">Jilin Chen</a>, <a href="/search/cs?searchtype=author&query=Pitler%2C+E">Emily Pitler</a>, <a href="/search/cs?searchtype=author&query=Lillicrap%2C+T">Timothy Lillicrap</a>, <a href="/search/cs?searchtype=author&query=Lazaridou%2C+A">Angeliki Lazaridou</a>, <a href="/search/cs?searchtype=author&query=Firat%2C+O">Orhan Firat</a>, <a href="/search/cs?searchtype=author&query=Molloy%2C+J">James Molloy</a>, <a href="/search/cs?searchtype=author&query=Isard%2C+M">Michael Isard</a>, <a href="/search/cs?searchtype=author&query=Barham%2C+P+R">Paul R. Barham</a>, <a href="/search/cs?searchtype=author&query=Hennigan%2C+T">Tom Hennigan</a>, <a href="/search/cs?searchtype=author&query=Lee%2C+B">Benjamin Lee</a> , et al. (1325 additional authors not shown) </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2312.11805v4-abstract-short" style="display: inline;"> This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. The Gemini family consists of Ultra, Pro, and Nano sizes, suitable for applications ranging from complex reasoning tasks to on-device memory-constrained use-cases. Evaluation on a broad range of benchmarks shows that our most-capable Gemini Ultr… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2312.11805v4-abstract-full').style.display = 'inline'; document.getElementById('2312.11805v4-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2312.11805v4-abstract-full" style="display: none;"> This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. The Gemini family consists of Ultra, Pro, and Nano sizes, suitable for applications ranging from complex reasoning tasks to on-device memory-constrained use-cases. Evaluation on a broad range of benchmarks shows that our most-capable Gemini Ultra model advances the state of the art in 30 of 32 of these benchmarks - notably being the first model to achieve human-expert performance on the well-studied exam benchmark MMLU, and improving the state of the art in every one of the 20 multimodal benchmarks we examined. We believe that the new capabilities of the Gemini family in cross-modal reasoning and language understanding will enable a wide variety of use cases. We discuss our approach toward post-training and deploying Gemini models responsibly to users through services including Gemini, Gemini Advanced, Google AI Studio, and Cloud Vertex AI. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2312.11805v4-abstract-full').style.display = 'none'; document.getElementById('2312.11805v4-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 17 June, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 18 December, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> December 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2308.07481">arXiv:2308.07481</a> <span> [<a href="https://arxiv.org/pdf/2308.07481">pdf</a>, <a href="https://arxiv.org/format/2308.07481">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Instrumentation and Methods for Astrophysics">astro-ph.IM</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="Image and Video Processing">eess.IV</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Space Physics">physics.space-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/10.1038/s41598-024-51659-7">10.1038/s41598-024-51659-7 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Space Object Identification and Classification from Hyperspectral Material Analysis </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Vasile%2C+M">Massimiliano Vasile</a>, <a href="/search/cs?searchtype=author&query=Walker%2C+L">Lewis Walker</a>, <a href="/search/cs?searchtype=author&query=Campbell%2C+A">Andrew Campbell</a>, <a href="/search/cs?searchtype=author&query=Marto%2C+S">Simao Marto</a>, <a href="/search/cs?searchtype=author&query=Murray%2C+P">Paul Murray</a>, <a href="/search/cs?searchtype=author&query=Marshall%2C+S">Stephen Marshall</a>, <a href="/search/cs?searchtype=author&query=Savitski%2C+V">Vasili Savitski</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="2308.07481v1-abstract-short" style="display: inline;"> This paper presents a data processing pipeline designed to extract information from the hyperspectral signature of unknown space objects. The methodology proposed in this paper determines the material composition of space objects from single pixel images. Two techniques are used for material identification and classification: one based on machine learning and the other based on a least square matc… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2308.07481v1-abstract-full').style.display = 'inline'; document.getElementById('2308.07481v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2308.07481v1-abstract-full" style="display: none;"> This paper presents a data processing pipeline designed to extract information from the hyperspectral signature of unknown space objects. The methodology proposed in this paper determines the material composition of space objects from single pixel images. Two techniques are used for material identification and classification: one based on machine learning and the other based on a least square match with a library of known spectra. From this information, a supervised machine learning algorithm is used to classify the object into one of several categories based on the detection of materials on the object. The behaviour of the material classification methods is investigated under non-ideal circumstances, to determine the effect of weathered materials, and the behaviour when the training library is missing a material that is present in the object being observed. Finally the paper will present some preliminary results on the identification and classification of space objects. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2308.07481v1-abstract-full').style.display = 'none'; document.getElementById('2308.07481v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 14 August, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 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">30 pages, 24 figures</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">MSC Class:</span> 68; 70 <span class="has-text-black-bis has-text-weight-semibold">ACM Class:</span> I.2.0; I.2.10 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2308.00862">arXiv:2308.00862</a> <span> [<a href="https://arxiv.org/pdf/2308.00862">pdf</a>, <a href="https://arxiv.org/ps/2308.00862">ps</a>, <a href="https://arxiv.org/format/2308.00862">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computers and Society">cs.CY</span> </div> </div> <p class="title is-5 mathjax"> Confidence-Building Measures for Artificial Intelligence: Workshop Proceedings </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Shoker%2C+S">Sarah Shoker</a>, <a href="/search/cs?searchtype=author&query=Reddie%2C+A">Andrew Reddie</a>, <a href="/search/cs?searchtype=author&query=Barrington%2C+S">Sarah Barrington</a>, <a href="/search/cs?searchtype=author&query=Booth%2C+R">Ruby Booth</a>, <a href="/search/cs?searchtype=author&query=Brundage%2C+M">Miles Brundage</a>, <a href="/search/cs?searchtype=author&query=Chahal%2C+H">Husanjot Chahal</a>, <a href="/search/cs?searchtype=author&query=Depp%2C+M">Michael Depp</a>, <a href="/search/cs?searchtype=author&query=Drexel%2C+B">Bill Drexel</a>, <a href="/search/cs?searchtype=author&query=Gupta%2C+R">Ritwik Gupta</a>, <a href="/search/cs?searchtype=author&query=Favaro%2C+M">Marina Favaro</a>, <a href="/search/cs?searchtype=author&query=Hecla%2C+J">Jake Hecla</a>, <a href="/search/cs?searchtype=author&query=Hickey%2C+A">Alan Hickey</a>, <a href="/search/cs?searchtype=author&query=Konaev%2C+M">Margarita Konaev</a>, <a href="/search/cs?searchtype=author&query=Kumar%2C+K">Kirthi Kumar</a>, <a href="/search/cs?searchtype=author&query=Lambert%2C+N">Nathan Lambert</a>, <a href="/search/cs?searchtype=author&query=Lohn%2C+A">Andrew Lohn</a>, <a href="/search/cs?searchtype=author&query=O%27Keefe%2C+C">Cullen O'Keefe</a>, <a href="/search/cs?searchtype=author&query=Rajani%2C+N">Nazneen Rajani</a>, <a href="/search/cs?searchtype=author&query=Sellitto%2C+M">Michael Sellitto</a>, <a href="/search/cs?searchtype=author&query=Trager%2C+R">Robert Trager</a>, <a href="/search/cs?searchtype=author&query=Walker%2C+L">Leah Walker</a>, <a href="/search/cs?searchtype=author&query=Wehsener%2C+A">Alexa Wehsener</a>, <a href="/search/cs?searchtype=author&query=Young%2C+J">Jessica Young</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="2308.00862v2-abstract-short" style="display: inline;"> Foundation models could eventually introduce several pathways for undermining state security: accidents, inadvertent escalation, unintentional conflict, the proliferation of weapons, and the interference with human diplomacy are just a few on a long list. The Confidence-Building Measures for Artificial Intelligence workshop hosted by the Geopolitics Team at OpenAI and the Berkeley Risk and Securit… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2308.00862v2-abstract-full').style.display = 'inline'; document.getElementById('2308.00862v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2308.00862v2-abstract-full" style="display: none;"> Foundation models could eventually introduce several pathways for undermining state security: accidents, inadvertent escalation, unintentional conflict, the proliferation of weapons, and the interference with human diplomacy are just a few on a long list. The Confidence-Building Measures for Artificial Intelligence workshop hosted by the Geopolitics Team at OpenAI and the Berkeley Risk and Security Lab at the University of California brought together a multistakeholder group to think through the tools and strategies to mitigate the potential risks introduced by foundation models to international security. Originating in the Cold War, confidence-building measures (CBMs) are actions that reduce hostility, prevent conflict escalation, and improve trust between parties. The flexibility of CBMs make them a key instrument for navigating the rapid changes in the foundation model landscape. Participants identified the following CBMs that directly apply to foundation models and which are further explained in this conference proceedings: 1. crisis hotlines 2. incident sharing 3. model, transparency, and system cards 4. content provenance and watermarks 5. collaborative red teaming and table-top exercises and 6. dataset and evaluation sharing. Because most foundation model developers are non-government entities, many CBMs will need to involve a wider stakeholder community. These measures can be implemented either by AI labs or by relevant government actors. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2308.00862v2-abstract-full').style.display = 'none'; document.getElementById('2308.00862v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 3 August, 2023; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 1 August, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2307.14834">arXiv:2307.14834</a> <span> [<a href="https://arxiv.org/pdf/2307.14834">pdf</a>, <a href="https://arxiv.org/format/2307.14834">other</a>] </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="Systems and Control">eess.SY</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/10.1109/IROS55552.2023.10341695">10.1109/IROS55552.2023.10341695 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Disturbance Preview for Nonlinear Model Predictive Trajectory Tracking of Underwater Vehicles in Wave Dominated Environments </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Walker%2C+K+L">Kyle L. Walker</a>, <a href="/search/cs?searchtype=author&query=Giorgio-Serchi%2C+F">Francesco Giorgio-Serchi</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="2307.14834v1-abstract-short" style="display: inline;"> Operating in the near-vicinity of marine energy devices poses significant challenges to the control of underwater vehicles, predominantly due to the presence of large magnitude wave disturbances causing hazardous state perturbations. Approaches to tackle this problem have varied, but one promising solution is to adopt predictive control methods. Given the predictable nature of ocean waves, the pot… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2307.14834v1-abstract-full').style.display = 'inline'; document.getElementById('2307.14834v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2307.14834v1-abstract-full" style="display: none;"> Operating in the near-vicinity of marine energy devices poses significant challenges to the control of underwater vehicles, predominantly due to the presence of large magnitude wave disturbances causing hazardous state perturbations. Approaches to tackle this problem have varied, but one promising solution is to adopt predictive control methods. Given the predictable nature of ocean waves, the potential exists to incorporate disturbance estimations directly within the plant model; this requires inclusion of a wave predictor to provide online preview information. To this end, this paper presents a Nonlinear Model Predictive Controller with an integrated Deterministic Sea Wave Predictor for trajectory tracking of underwater vehicles. State information is obtained through an Extended Kalman Filter, forming a complete closed-loop strategy and facilitating online wave load estimations. The strategy is compared to a similar feed-forward disturbance mitigation scheme, showing mean performance improvements of 51% in positional error and 44.5% in attitude error. The preliminary results presented here provide strong evidence of the proposed method's high potential to effectively mitigate disturbances, facilitating accurate tracking performance even in the presence of high wave loading. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2307.14834v1-abstract-full').style.display = 'none'; document.getElementById('2307.14834v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 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">To be presented at IROS 2023, Detroit, USA</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2306.06194">arXiv:2306.06194</a> <span> [<a href="https://arxiv.org/pdf/2306.06194">pdf</a>, <a href="https://arxiv.org/format/2306.06194">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> </div> <p class="title is-5 mathjax"> Share, Collaborate, Benchmark: Advancing Travel Demand Research through rigorous open-source collaboration </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Caicedo%2C+J+D">Juan D. Caicedo</a>, <a href="/search/cs?searchtype=author&query=Guirado%2C+C">Carlos Guirado</a>, <a href="/search/cs?searchtype=author&query=Gonz%C3%A1lez%2C+M+C">Marta C. Gonz谩lez</a>, <a href="/search/cs?searchtype=author&query=Walker%2C+J+L">Joan L. Walker</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="2306.06194v2-abstract-short" style="display: inline;"> This research foregrounds general practices in travel demand research, emphasizing the need to change our ways. A critical barrier preventing travel demand literature from effectively informing policy is the volume of publications without clear, consolidated benchmarks, making it difficult for researchers and policymakers to gather insights and use models to guide decision-making. By emphasizing r… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.06194v2-abstract-full').style.display = 'inline'; document.getElementById('2306.06194v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2306.06194v2-abstract-full" style="display: none;"> This research foregrounds general practices in travel demand research, emphasizing the need to change our ways. A critical barrier preventing travel demand literature from effectively informing policy is the volume of publications without clear, consolidated benchmarks, making it difficult for researchers and policymakers to gather insights and use models to guide decision-making. By emphasizing reproducibility and open collaboration, we aim to enhance the reliability and policy relevance of travel demand research. We present a collaborative infrastructure for transit demand prediction models, focusing on their performance during highly dynamic conditions like the COVID-19 pandemic. Drawing from over 300 published papers, we develop an open-source infrastructure with five common methodologies and assess their performance under stable and dynamic conditions. We found that the prediction error for the LSTM deep learning approach stabilized at a mean arctangent absolute percentage error (MAAPE) of about 0.12 within 1.5 months, whereas other models continued to exhibit higher error rates even a year into the pandemic. If research practices had prioritized reproducibility before the COVID-19 pandemic, transit agencies would have had clearer guidance on the best forecasting methods and quickly identified those best suited for pandemic conditions to inform operations in response to changes in transit demand. The aim of this open-source codebase is to lower the barrier for other researchers to replicate, reproduce models and build upon findings. We encourage researchers to test their own modeling approaches on this benchmarking platform, challenge the analyses conducted in this paper, and develop model specifications that can outperform those evaluated here. Further, collaborative research approaches must be expanded across travel demand modeling if we wish to impact policy and planning. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.06194v2-abstract-full').style.display = 'none'; document.getElementById('2306.06194v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 14 July, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 9 June, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 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">18 pages, 8 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2304.05222">arXiv:2304.05222</a> <span> [<a href="https://arxiv.org/pdf/2304.05222">pdf</a>, <a href="https://arxiv.org/format/2304.05222">other</a>] </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 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/10.1109/OCEANSLimerick52467.2023.10244350">10.1109/OCEANSLimerick52467.2023.10244350 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Feed-forward Disturbance Compensation for Station Keeping in Wave-dominated Environments </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Walker%2C+K+L">Kyle L. Walker</a>, <a href="/search/cs?searchtype=author&query=Stokes%2C+A+A">Adam A. Stokes</a>, <a href="/search/cs?searchtype=author&query=Kiprakis%2C+A">Aristides Kiprakis</a>, <a href="/search/cs?searchtype=author&query=Giorgio-Serchi%2C+F">Francesco Giorgio-Serchi</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="2304.05222v1-abstract-short" style="display: inline;"> When deploying robots in shallow ocean waters, wave disturbances can be significant, highly dynamic and pose problems when operating near structures; this is a key limitation of current control strategies, restricting the range of conditions in which subsea vehicles can be deployed. To improve dynamic control and offer a higher level of robustness, this work proposes a Cascaded Proportional-Deriva… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2304.05222v1-abstract-full').style.display = 'inline'; document.getElementById('2304.05222v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2304.05222v1-abstract-full" style="display: none;"> When deploying robots in shallow ocean waters, wave disturbances can be significant, highly dynamic and pose problems when operating near structures; this is a key limitation of current control strategies, restricting the range of conditions in which subsea vehicles can be deployed. To improve dynamic control and offer a higher level of robustness, this work proposes a Cascaded Proportional-Derivative (C-PD) with Feed-forward (FF) control scheme for disturbance mitigation, exploring the concept of explicitly using disturbance estimations to counteract state perturbations. Results demonstrate that the proposed controller is capable of higher performance in contrast to a standard C-PD controller, with an average reduction of ~48% witnessed across various sea states. Additional analysis also investigated performance when considering coarse estimations featuring inaccuracies; average improvements of ~17% demonstrate the effectiveness of the proposed strategy to handle these uncertainties. The proposal in this work shows promise for improved control without a drastic increase in required computing power; if coupled with sufficient sensors, state estimation techniques and prediction algorithms, utilising feed-forward compensating control actions offers a potential solution to improve vehicle control under wave-induced disturbances. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2304.05222v1-abstract-full').style.display = 'none'; document.getElementById('2304.05222v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 11 April, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> April 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">To published in proceedings of Oceans 2023: Limerick</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2201.06068">arXiv:2201.06068</a> <span> [<a href="https://arxiv.org/pdf/2201.06068">pdf</a>] </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="Computers and Society">cs.CY</span> <span class="tag is-small is-grey 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="Social and Information Networks">cs.SI</span> </div> </div> <p class="title is-5 mathjax"> Zero Botnets: An Observe-Pursue-Counter Approach </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Kepner%2C+J">Jeremy Kepner</a>, <a href="/search/cs?searchtype=author&query=Bernays%2C+J">Jonathan Bernays</a>, <a href="/search/cs?searchtype=author&query=Buckley%2C+S">Stephen Buckley</a>, <a href="/search/cs?searchtype=author&query=Cho%2C+K">Kenjiro Cho</a>, <a href="/search/cs?searchtype=author&query=Conrad%2C+C">Cary Conrad</a>, <a href="/search/cs?searchtype=author&query=Daigle%2C+L">Leslie Daigle</a>, <a href="/search/cs?searchtype=author&query=Erhardt%2C+K">Keeley Erhardt</a>, <a href="/search/cs?searchtype=author&query=Gadepally%2C+V">Vijay Gadepally</a>, <a href="/search/cs?searchtype=author&query=Greene%2C+B">Barry Greene</a>, <a href="/search/cs?searchtype=author&query=Jones%2C+M">Michael Jones</a>, <a href="/search/cs?searchtype=author&query=Knake%2C+R">Robert Knake</a>, <a href="/search/cs?searchtype=author&query=Maggs%2C+B">Bruce Maggs</a>, <a href="/search/cs?searchtype=author&query=Michaleas%2C+P">Peter Michaleas</a>, <a href="/search/cs?searchtype=author&query=Meiners%2C+C">Chad Meiners</a>, <a href="/search/cs?searchtype=author&query=Morris%2C+A">Andrew Morris</a>, <a href="/search/cs?searchtype=author&query=Pentland%2C+A">Alex Pentland</a>, <a href="/search/cs?searchtype=author&query=Pisharody%2C+S">Sandeep Pisharody</a>, <a href="/search/cs?searchtype=author&query=Powazek%2C+S">Sarah Powazek</a>, <a href="/search/cs?searchtype=author&query=Prout%2C+A">Andrew Prout</a>, <a href="/search/cs?searchtype=author&query=Reiner%2C+P">Philip Reiner</a>, <a href="/search/cs?searchtype=author&query=Suzuki%2C+K">Koichi Suzuki</a>, <a href="/search/cs?searchtype=author&query=Takahashi%2C+K">Kenji Takahashi</a>, <a href="/search/cs?searchtype=author&query=Tauber%2C+T">Tony Tauber</a>, <a href="/search/cs?searchtype=author&query=Walker%2C+L">Leah Walker</a>, <a href="/search/cs?searchtype=author&query=Stetson%2C+D">Douglas Stetson</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="2201.06068v1-abstract-short" style="display: inline;"> Adversarial Internet robots (botnets) represent a growing threat to the safe use and stability of the Internet. Botnets can play a role in launching adversary reconnaissance (scanning and phishing), influence operations (upvoting), and financing operations (ransomware, market manipulation, denial of service, spamming, and ad click fraud) while obfuscating tailored tactical operations. Reducing the… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2201.06068v1-abstract-full').style.display = 'inline'; document.getElementById('2201.06068v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2201.06068v1-abstract-full" style="display: none;"> Adversarial Internet robots (botnets) represent a growing threat to the safe use and stability of the Internet. Botnets can play a role in launching adversary reconnaissance (scanning and phishing), influence operations (upvoting), and financing operations (ransomware, market manipulation, denial of service, spamming, and ad click fraud) while obfuscating tailored tactical operations. Reducing the presence of botnets on the Internet, with the aspirational target of zero, is a powerful vision for galvanizing policy action. Setting a global goal, encouraging international cooperation, creating incentives for improving networks, and supporting entities for botnet takedowns are among several policies that could advance this goal. These policies raise significant questions regarding proper authorities/access that cannot be answered in the abstract. Systems analysis has been widely used in other domains to achieve sufficient detail to enable these questions to be dealt with in concrete terms. Defeating botnets using an observe-pursue-counter architecture is analyzed, the technical feasibility is affirmed, and the authorities/access questions are significantly narrowed. Recommended next steps include: supporting the international botnet takedown community, expanding network observatories, enhancing the underlying network science at scale, conducting detailed systems analysis, and developing appropriate policy frameworks. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2201.06068v1-abstract-full').style.display = 'none'; document.getElementById('2201.06068v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 16 January, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 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">26 pages, 13 figures, 2 tables, 72 references, submitted to PlosOne</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Report number:</span> Harvard Belfer Center Report (2021 June) </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2108.07709">arXiv:2108.07709</a> <span> [<a href="https://arxiv.org/pdf/2108.07709">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computers and Society">cs.CY</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</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/10.1097/JPA.0000000000000513">10.1097/JPA.0000000000000513 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> The application of adaptive minimum match k-nearest neighbors to identify at-risk students in health professions education </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Kumar%2C+A">Anshul Kumar</a>, <a href="/search/cs?searchtype=author&query=DiJohnson%2C+T">Taylor DiJohnson</a>, <a href="/search/cs?searchtype=author&query=Edwards%2C+R">Roger Edwards</a>, <a href="/search/cs?searchtype=author&query=Walker%2C+L">Lisa Walker</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="2108.07709v3-abstract-short" style="display: inline;"> Purpose: When a learner fails to reach a milestone, educators often wonder if there had been any warning signs that could have allowed them to intervene sooner. Machine learning can predict which students are at risk of failing a high-stakes certification exam. If predictions can be made well in advance of the exam, then educators can meaningfully intervene before students take the exam to reduce… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2108.07709v3-abstract-full').style.display = 'inline'; document.getElementById('2108.07709v3-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2108.07709v3-abstract-full" style="display: none;"> Purpose: When a learner fails to reach a milestone, educators often wonder if there had been any warning signs that could have allowed them to intervene sooner. Machine learning can predict which students are at risk of failing a high-stakes certification exam. If predictions can be made well in advance of the exam, then educators can meaningfully intervene before students take the exam to reduce the chances of a failing score. Methods: Using already-collected, first-year student assessment data from five cohorts in a Master of Physician Assistant Studies program, the authors implement an "adaptive minimum match" version of the k-nearest neighbors algorithm (AMMKNN), using changing numbers of neighbors to predict each student's future exam scores on the Physician Assistant National Certifying Examination (PANCE). Validation occurred in two ways: Leave-one-out cross-validation (LOOCV) and evaluating the predictions in a new cohort. Results: AMMKNN achieved an accuracy of 93% in LOOCV. AMMKNN generates a predicted PANCE score for each student, one year before they are scheduled to take the exam. Students can then be classified into extra support, optional extra support, or no extra support groups. The educator then has one year to provide the appropriate customized support to each category of student. Conclusions: Predictive analytics can identify at-risk students, so they can receive additional support or remediation when preparing for high-stakes certification exams. Educators can use the included methods and code to generate predicted test outcomes for students. The authors recommend that educators use this or similar predictive methods responsibly and transparently, as one of many tools used to support students. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2108.07709v3-abstract-full').style.display = 'none'; document.getElementById('2108.07709v3-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 9 August, 2022; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 4 August, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2021. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> JPAE 34(3):p 171-177, 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/1506.03782">arXiv:1506.03782</a> <span> [<a href="https://arxiv.org/pdf/1506.03782">pdf</a>, <a href="https://arxiv.org/ps/1506.03782">ps</a>, <a href="https://arxiv.org/format/1506.03782">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</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"> Matched Metrics and Channels </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Firer%2C+M">Marcelo Firer</a>, <a href="/search/cs?searchtype=author&query=Walker%2C+J+L">Judy L. Walker</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="1506.03782v1-abstract-short" style="display: inline;"> The most common decision criteria for decoding are maximum likelihood decoding and nearest neighbor decoding. It is well-known that maximum likelihood decoding coincides with nearest neighbor decoding with respect to the Hamming metric on the binary symmetric channel. In this work we study channels and metrics for which those two criteria do and do not coincide for general codes. </span> <span class="abstract-full has-text-grey-dark mathjax" id="1506.03782v1-abstract-full" style="display: none;"> The most common decision criteria for decoding are maximum likelihood decoding and nearest neighbor decoding. It is well-known that maximum likelihood decoding coincides with nearest neighbor decoding with respect to the Hamming metric on the binary symmetric channel. In this work we study channels and metrics for which those two criteria do and do not coincide for general codes. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1506.03782v1-abstract-full').style.display = 'none'; document.getElementById('1506.03782v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 11 June, 2015; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2015. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">MSC Class:</span> 68P30 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1212.5188">arXiv:1212.5188</a> <span> [<a href="https://arxiv.org/pdf/1212.5188">pdf</a>, <a href="https://arxiv.org/format/1212.5188">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Neurons and Cognition">q-bio.NC</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> </div> </div> <p class="title is-5 mathjax"> Combinatorial neural codes from a mathematical coding theory perspective </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Curto%2C+C">Carina Curto</a>, <a href="/search/cs?searchtype=author&query=Itskov%2C+V">Vladimir Itskov</a>, <a href="/search/cs?searchtype=author&query=Morrison%2C+K">Katherine Morrison</a>, <a href="/search/cs?searchtype=author&query=Roth%2C+Z">Zachary Roth</a>, <a href="/search/cs?searchtype=author&query=Walker%2C+J+L">Judy L. Walker</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="1212.5188v1-abstract-short" style="display: inline;"> Shannon's seminal 1948 work gave rise to two distinct areas of research: information theory and mathematical coding theory. While information theory has had a strong influence on theoretical neuroscience, ideas from mathematical coding theory have received considerably less attention. Here we take a new look at combinatorial neural codes from a mathematical coding theory perspective, examining the… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1212.5188v1-abstract-full').style.display = 'inline'; document.getElementById('1212.5188v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1212.5188v1-abstract-full" style="display: none;"> Shannon's seminal 1948 work gave rise to two distinct areas of research: information theory and mathematical coding theory. While information theory has had a strong influence on theoretical neuroscience, ideas from mathematical coding theory have received considerably less attention. Here we take a new look at combinatorial neural codes from a mathematical coding theory perspective, examining the error correction capabilities of familiar receptive field codes (RF codes). We find, perhaps surprisingly, that the high levels of redundancy present in these codes does not support accurate error correction, although the error-correcting performance of RF codes "catches up" to that of random comparison codes when a small tolerance to error is introduced. On the other hand, RF codes are good at reflecting distances between represented stimuli, while the random comparison codes are not. We suggest that a compromise in error-correcting capability may be a necessary price to pay for a neural code whose structure serves not only error correction, but must also reflect relationships between stimuli. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1212.5188v1-abstract-full').style.display = 'none'; document.getElementById('1212.5188v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 20 December, 2012; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> December 2012. </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">26 pages, 8 figures</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Neural Computation, Vol 25(7), pp. 1891-1925, 2013 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/cs/0508049">arXiv:cs/0508049</a> <span> [<a href="https://arxiv.org/pdf/cs/0508049">pdf</a>, <a href="https://arxiv.org/ps/cs/0508049">ps</a>, <a href="https://arxiv.org/format/cs/0508049">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</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"> Characterizations of Pseudo-Codewords of LDPC Codes </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Koetter%2C+R">Ralf Koetter</a>, <a href="/search/cs?searchtype=author&query=Li%2C+W+W">Wen-Ching W. Li</a>, <a href="/search/cs?searchtype=author&query=Vontobel%2C+P+O">Pascal O. Vontobel</a>, <a href="/search/cs?searchtype=author&query=Walker%2C+J+L">Judy L. Walker</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="cs/0508049v3-abstract-short" style="display: inline;"> An important property of high-performance, low complexity codes is the existence of highly efficient algorithms for their decoding. Many of the most efficient, recent graph-based algorithms, e.g. message passing algorithms and decoding based on linear programming, crucially depend on the efficient representation of a code in a graphical model. In order to understand the performance of these algo… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('cs/0508049v3-abstract-full').style.display = 'inline'; document.getElementById('cs/0508049v3-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="cs/0508049v3-abstract-full" style="display: none;"> An important property of high-performance, low complexity codes is the existence of highly efficient algorithms for their decoding. Many of the most efficient, recent graph-based algorithms, e.g. message passing algorithms and decoding based on linear programming, crucially depend on the efficient representation of a code in a graphical model. In order to understand the performance of these algorithms, we argue for the characterization of codes in terms of a so called fundamental cone in Euclidean space which is a function of a given parity check matrix of a code, rather than of the code itself. We give a number of properties of this fundamental cone derived from its connection to unramified covers of the graphical models on which the decoding algorithms operate. For the class of cycle codes, these developments naturally lead to a characterization of the fundamental polytope as the Newton polytope of the Hashimoto edge zeta function of the underlying graph. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('cs/0508049v3-abstract-full').style.display = 'none'; document.getElementById('cs/0508049v3-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 17 August, 2005; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 8 August, 2005; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2005. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Submitted, August 2005</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/cs/0502033">arXiv:cs/0502033</a> <span> [<a href="https://arxiv.org/pdf/cs/0502033">pdf</a>, <a href="https://arxiv.org/ps/cs/0502033">ps</a>, <a href="https://arxiv.org/format/cs/0502033">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> </div> </div> <p class="title is-5 mathjax"> Pseudo-Codewords of Cycle Codes via Zeta Functions </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Koetter%2C+R">Ralf Koetter</a>, <a href="/search/cs?searchtype=author&query=Li%2C+W+W">Wen-Ching W. Li</a>, <a href="/search/cs?searchtype=author&query=Vontobel%2C+P+O">Pascal O. Vontobel</a>, <a href="/search/cs?searchtype=author&query=Walker%2C+J+L">Judy L. Walker</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="cs/0502033v1-abstract-short" style="display: inline;"> Cycle codes are a special case of low-density parity-check (LDPC) codes and as such can be decoded using an iterative message-passing decoding algorithm on the associated Tanner graph. The existence of pseudo-codewords is known to cause the decoding algorithm to fail in certain instances. In this paper, we draw a connection between pseudo-codewords of cycle codes and the so-called edge zeta func… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('cs/0502033v1-abstract-full').style.display = 'inline'; document.getElementById('cs/0502033v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="cs/0502033v1-abstract-full" style="display: none;"> Cycle codes are a special case of low-density parity-check (LDPC) codes and as such can be decoded using an iterative message-passing decoding algorithm on the associated Tanner graph. The existence of pseudo-codewords is known to cause the decoding algorithm to fail in certain instances. In this paper, we draw a connection between pseudo-codewords of cycle codes and the so-called edge zeta function of the associated normal graph and show how the Newton polyhedron of the zeta function equals the fundamental cone of the code, which plays a crucial role in characterizing the performance of iterative decoding algorithms. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('cs/0502033v1-abstract-full').style.display = 'none'; document.getElementById('cs/0502033v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 5 February, 2005; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2005. </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">Presented at Information Theory Workshop (ITW), San Antonio, TX, 2004</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">ACM Class:</span> E.4 </p> </li> </ol> <div class="is-hidden-tablet">  <span class="help" style="display: inline-block;"><a href="https://github.com/arXiv/arxiv-search/releases">Search v0.5.6 released 2020-02-24</a>  </span> </div> </div> </main> <footer> <div class="columns is-desktop" role="navigation" aria-label="Secondary">  <div class="column"> <div class="columns"> <div class="column"> <ul class="nav-spaced"> <li><a href="https://info.arxiv.org/about">About</a></li> <li><a href="https://info.arxiv.org/help">Help</a></li> </ul> </div> <div class="column"> <ul class="nav-spaced"> <li> <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" class="icon filter-black" role="presentation"><title>contact arXiv</title><desc>Click here to contact arXiv</desc><path d="M502.3 190.8c3.9-3.1 9.7-.2 9.7 4.7V400c0 26.5-21.5 48-48 48H48c-26.5 0-48-21.5-48-48V195.6c0-5 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