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</li><li> <a href="/list/cs.LG/recent?skip=667&show=50"> Mon, 17 Mar 2025 </a> </li></ul> <p>See today's <a id="new-cs.LG" aria-labelledby="new-cs.LG" href="/list/cs.LG/new">new</a> changes</p> <div class='paging'>Total of 807 entries : <span>1-50</span> <a href=/list/cs.LG/recent?skip=50&show=50>51-100</a> <a href=/list/cs.LG/recent?skip=100&show=50>101-150</a> <a href=/list/cs.LG/recent?skip=150&show=50>151-200</a> <span>...</span> <a href=/list/cs.LG/recent?skip=800&show=50>801-807</a> </div> <div class='morefewer'>Showing up to 50 entries per page: <a href=/list/cs.LG/recent?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/cs.LG/recent?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/cs.LG/recent?skip=0&show=2000 rel="nofollow"> all</a> </div> <dl id='articles'> <h3>Fri, 21 Mar 2025 (showing first 50 of 126 entries )</h3> <dt> <a name='item1'>[1]</a> <a href ="/abs/2503.16401" title="Abstract" id="2503.16401"> arXiv:2503.16401 </a> [<a href="/pdf/2503.16401" title="Download PDF" id="pdf-2503.16401" aria-labelledby="pdf-2503.16401">pdf</a>, <a href="https://arxiv.org/html/2503.16401v1" title="View HTML" id="html-2503.16401" aria-labelledby="html-2503.16401" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16401" title="Other formats" id="oth-2503.16401" aria-labelledby="oth-2503.16401">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Exploring the Hidden Reasoning Process of Large Language Models by Misleading Them </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+G">Guanyu Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+P">Peiyang Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+T">Tianren Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+F">Feng Chen</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item2'>[2]</a> <a href ="/abs/2503.16400" title="Abstract" id="2503.16400"> arXiv:2503.16400 </a> [<a href="/pdf/2503.16400" title="Download PDF" id="pdf-2503.16400" aria-labelledby="pdf-2503.16400">pdf</a>, <a href="https://arxiv.org/html/2503.16400v1" title="View HTML" id="html-2503.16400" aria-labelledby="html-2503.16400" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16400" title="Other formats" id="oth-2503.16400" aria-labelledby="oth-2503.16400">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> ScalingNoise: Scaling Inference-Time Search for Generating Infinite Videos </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Yang,+H">Haolin Yang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tang,+F">Feilong Tang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hu,+M">Ming Hu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+Y">Yulong Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Guo,+J">Junjie Guo</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+Y">Yexin Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Peng,+Z">Zelin Peng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=He,+J">Junjun He</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ge,+Z">Zongyuan Ge</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Razzak,+I">Imran Razzak</a>, </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item3'>[3]</a> <a href ="/abs/2503.16395" title="Abstract" id="2503.16395"> arXiv:2503.16395 </a> [<a href="/pdf/2503.16395" title="Download PDF" id="pdf-2503.16395" aria-labelledby="pdf-2503.16395">pdf</a>, <a href="https://arxiv.org/html/2503.16395v1" title="View HTML" id="html-2503.16395" aria-labelledby="html-2503.16395" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16395" title="Other formats" id="oth-2503.16395" aria-labelledby="oth-2503.16395">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Truthful Elicitation of Imprecise Forecasts </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Singh,+A">Anurag Singh</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chau,+S+L">Siu Lun Chau</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Muandet,+K">Krikamol Muandet</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 32 pages, 3 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item4'>[4]</a> <a href ="/abs/2503.16364" title="Abstract" id="2503.16364"> arXiv:2503.16364 </a> [<a href="/pdf/2503.16364" title="Download PDF" id="pdf-2503.16364" aria-labelledby="pdf-2503.16364">pdf</a>, <a href="/format/2503.16364" title="Other formats" id="oth-2503.16364" aria-labelledby="oth-2503.16364">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Neural Networks: According to the Principles of Grassmann Algebra </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Zarezadeh,+Z">Z. Zarezadeh</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zarezadeh,+N">N. Zarezadeh</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI) </div> </div> </dd> <dt> <a name='item5'>[5]</a> <a href ="/abs/2503.16363" title="Abstract" id="2503.16363"> arXiv:2503.16363 </a> [<a href="/pdf/2503.16363" title="Download PDF" id="pdf-2503.16363" aria-labelledby="pdf-2503.16363">pdf</a>, <a href="https://arxiv.org/html/2503.16363v1" title="View HTML" id="html-2503.16363" aria-labelledby="html-2503.16363" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16363" title="Other formats" id="oth-2503.16363" aria-labelledby="oth-2503.16363">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Probabilistic Quantum SVM Training on Ising Machine </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=He,+H">Haoqi He</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xiao,+Y">Yan Xiao</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Quantum Physics (quant-ph) </div> </div> </dd> <dt> <a name='item6'>[6]</a> <a href ="/abs/2503.16351" title="Abstract" id="2503.16351"> arXiv:2503.16351 </a> [<a href="/pdf/2503.16351" title="Download PDF" id="pdf-2503.16351" aria-labelledby="pdf-2503.16351">pdf</a>, <a href="https://arxiv.org/html/2503.16351v1" title="View HTML" id="html-2503.16351" aria-labelledby="html-2503.16351" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16351" title="Other formats" id="oth-2503.16351" aria-labelledby="oth-2503.16351">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Lyra: An Efficient and Expressive Subquadratic Architecture for Modeling Biological Sequences </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Ramesh,+K">Krithik Ramesh</a> (1 and 2), <a href="https://arxiv.org/search/cs?searchtype=author&query=Siddiqui,+S+M">Sameed M. Siddiqui</a> (1 and 3), <a href="https://arxiv.org/search/cs?searchtype=author&query=Gu,+A">Albert Gu</a> (4), <a href="https://arxiv.org/search/cs?searchtype=author&query=Mitzenmacher,+M+D">Michael D. Mitzenmacher</a> (1 and 5), <a href="https://arxiv.org/search/cs?searchtype=author&query=Sabeti,+P+C">Pardis C. Sabeti</a> (1 and 6 and 7 and 8) ((1) Broad Institute of MIT and Harvard, (2) Massachusetts Institute of Technology, (3) Computational and Systems Biology Program, Massachusetts Institute of Technology, (4) Machine Learning Department, Carnegie Mellon University, (5) School of Engineering and Applied Sciences, Harvard University, (6) Department of Organismic and Evolutionary Biology, Harvard University, (7) Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, (8) Howard Hughes Medical Institute)</div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 53 pages, 5 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Genomics (q-bio.GN) </div> </div> </dd> <dt> <a name='item7'>[7]</a> <a href ="/abs/2503.16342" title="Abstract" id="2503.16342"> arXiv:2503.16342 </a> [<a href="/pdf/2503.16342" title="Download PDF" id="pdf-2503.16342" aria-labelledby="pdf-2503.16342">pdf</a>, <a href="https://arxiv.org/html/2503.16342v1" title="View HTML" id="html-2503.16342" aria-labelledby="html-2503.16342" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16342" title="Other formats" id="oth-2503.16342" aria-labelledby="oth-2503.16342">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> HiQ-Lip: The First Quantum-Classical Hierarchical Method for Global Lipschitz Constant Estimation of ReLU Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=He,+H">Haoqi He</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xiao,+Y">Yan Xiao</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Quantum Physics (quant-ph) </div> </div> </dd> <dt> <a name='item8'>[8]</a> <a href ="/abs/2503.16340" title="Abstract" id="2503.16340"> arXiv:2503.16340 </a> [<a href="/pdf/2503.16340" title="Download PDF" id="pdf-2503.16340" aria-labelledby="pdf-2503.16340">pdf</a>, <a href="https://arxiv.org/html/2503.16340v1" title="View HTML" id="html-2503.16340" aria-labelledby="html-2503.16340" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16340" title="Other formats" id="oth-2503.16340" aria-labelledby="oth-2503.16340">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Nonlinear action prediction models reveal multi-timescale locomotor control </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+W">Wei-Chen Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=De+Comite,+A">Antoine De Comite</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Daley,+M">Monica Daley</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Voloshina,+A">Alexandra Voloshina</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Seethapathi,+N">Nidhi Seethapathi</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Robotics (cs.RO) </div> </div> </dd> <dt> <a name='item9'>[9]</a> <a href ="/abs/2503.16328" title="Abstract" id="2503.16328"> arXiv:2503.16328 </a> [<a href="/pdf/2503.16328" title="Download PDF" id="pdf-2503.16328" aria-labelledby="pdf-2503.16328">pdf</a>, <a href="https://arxiv.org/html/2503.16328v1" title="View HTML" id="html-2503.16328" aria-labelledby="html-2503.16328" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16328" title="Other formats" id="oth-2503.16328" aria-labelledby="oth-2503.16328">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Knowledge-guided machine learning model with soil moisture for corn yield prediction under drought conditions </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+X">Xiaoyu Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xu,+Y">Yijia Xu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Huang,+J">Jingyi Huang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yang,+Z">Zhengwei Yang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+Z">Zhou Zhang</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI) </div> </div> </dd> <dt> <a name='item10'>[10]</a> <a href ="/abs/2503.16316" title="Abstract" id="2503.16316"> arXiv:2503.16316 </a> [<a href="/pdf/2503.16316" title="Download PDF" id="pdf-2503.16316" aria-labelledby="pdf-2503.16316">pdf</a>, <a href="https://arxiv.org/html/2503.16316v1" title="View HTML" id="html-2503.16316" aria-labelledby="html-2503.16316" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16316" title="Other formats" id="oth-2503.16316" aria-labelledby="oth-2503.16316">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> On the Cone Effect in the Learning Dynamics </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Zhou,+Z">Zhanpeng Zhou</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yang,+Y">Yongyi Yang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ren,+J">Jie Ren</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sugiyama,+M">Mahito Sugiyama</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yan,+J">Junchi Yan</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted by ICLR 2025 workshop DeLTa </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item11'>[11]</a> <a href ="/abs/2503.16311" title="Abstract" id="2503.16311"> arXiv:2503.16311 </a> [<a href="/pdf/2503.16311" title="Download PDF" id="pdf-2503.16311" aria-labelledby="pdf-2503.16311">pdf</a>, <a href="https://arxiv.org/html/2503.16311v1" title="View HTML" id="html-2503.16311" aria-labelledby="html-2503.16311" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16311" title="Other formats" id="oth-2503.16311" aria-labelledby="oth-2503.16311">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Structured-Noise Masked Modeling for Video, Audio and Beyond </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Bhowmik,+A">Aritra Bhowmik</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Thoker,+F+M">Fida Mohammad Thoker</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hinojosa,+C">Carlos Hinojosa</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ghanem,+B">Bernard Ghanem</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Snoek,+C+G+M">Cees G. M. Snoek</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Sound (cs.SD) </div> </div> </dd> <dt> <a name='item12'>[12]</a> <a href ="/abs/2503.16286" title="Abstract" id="2503.16286"> arXiv:2503.16286 </a> [<a href="/pdf/2503.16286" title="Download PDF" id="pdf-2503.16286" aria-labelledby="pdf-2503.16286">pdf</a>, <a href="https://arxiv.org/html/2503.16286v1" title="View HTML" id="html-2503.16286" aria-labelledby="html-2503.16286" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16286" title="Other formats" id="oth-2503.16286" aria-labelledby="oth-2503.16286">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Explainable Graph-theoretical Machine Learning: with Application to Alzheimer's Disease Prediction </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Baghirova,+N">Narmina Baghirova</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=V%C5%A9,+D">Duy-Thanh V农</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Can,+D">Duy-Cat Can</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Diaz,+C+S">Christelle Schneuwly Diaz</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bodlet,+J">Julien Bodlet</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Blanc,+G">Guillaume Blanc</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hrusanov,+G">Georgi Hrusanov</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ries,+B">Bernard Ries</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ch%C3%A9n,+O+Y">Oliver Y. Ch茅n</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item13'>[13]</a> <a href ="/abs/2503.16278" title="Abstract" id="2503.16278"> arXiv:2503.16278 </a> [<a href="/pdf/2503.16278" title="Download PDF" id="pdf-2503.16278" aria-labelledby="pdf-2503.16278">pdf</a>, <a href="https://arxiv.org/html/2503.16278v1" title="View HTML" id="html-2503.16278" aria-labelledby="html-2503.16278" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16278" title="Other formats" id="oth-2503.16278" aria-labelledby="oth-2503.16278">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Uni-3DAR: Unified 3D Generation and Understanding via Autoregression on Compressed Spatial Tokens </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Lu,+S">Shuqi Lu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lin,+H">Haowei Lin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yao,+L">Lin Yao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gao,+Z">Zhifeng Gao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ji,+X">Xiaohong Ji</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=E,+W">Weinan E</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+L">Linfeng Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ke,+G">Guolin Ke</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Materials Science (cond-mat.mtrl-sci); Biomolecules (q-bio.BM) </div> </div> </dd> <dt> <a name='item14'>[14]</a> <a href ="/abs/2503.16271" title="Abstract" id="2503.16271"> arXiv:2503.16271 </a> [<a href="/pdf/2503.16271" title="Download PDF" id="pdf-2503.16271" aria-labelledby="pdf-2503.16271">pdf</a>, <a href="https://arxiv.org/html/2503.16271v1" title="View HTML" id="html-2503.16271" aria-labelledby="html-2503.16271" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16271" title="Other formats" id="oth-2503.16271" aria-labelledby="oth-2503.16271">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Rethinking Robustness in Machine Learning: A Posterior Agreement Approach </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Carvalho,+J+B+S">Jo茫o Borges S. Carvalho</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Torcinovich,+A">Alessandro Torcinovich</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Rodriguez,+V+J">Victor Jimenez Rodriguez</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Cin%C3%A0,+A+E">Antonio E. Cin脿</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Cotrini,+C">Carlos Cotrini</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sch%C3%B6nherr,+L">Lea Sch枚nherr</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Buhmann,+J+M">Joachim M. Buhmann</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Preprint submitted to TMLR. 29 pages, 13 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item15'>[15]</a> <a href ="/abs/2503.16251" title="Abstract" id="2503.16251"> arXiv:2503.16251 </a> [<a href="/pdf/2503.16251" title="Download PDF" id="pdf-2503.16251" aria-labelledby="pdf-2503.16251">pdf</a>, <a href="https://arxiv.org/html/2503.16251v1" title="View HTML" id="html-2503.16251" aria-labelledby="html-2503.16251" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16251" title="Other formats" id="oth-2503.16251" aria-labelledby="oth-2503.16251">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> RESFL: An Uncertainty-Aware Framework for Responsible Federated Learning by Balancing Privacy, Fairness and Utility in Autonomous Vehicles </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Wasif,+D">Dawood Wasif</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Moore,+T+J">Terrence J. Moore</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Cho,+J">Jin-Hee Cho</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Submitted to PETS 2025 (under review) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Computer Vision and Pattern Recognition (cs.CV); Distributed, Parallel, and Cluster Computing (cs.DC); Emerging Technologies (cs.ET) </div> </div> </dd> <dt> <a name='item16'>[16]</a> <a href ="/abs/2503.16240" title="Abstract" id="2503.16240"> arXiv:2503.16240 </a> [<a href="/pdf/2503.16240" title="Download PDF" id="pdf-2503.16240" aria-labelledby="pdf-2503.16240">pdf</a>, <a href="https://arxiv.org/html/2503.16240v1" title="View HTML" id="html-2503.16240" aria-labelledby="html-2503.16240" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16240" title="Other formats" id="oth-2503.16240" aria-labelledby="oth-2503.16240">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Machine learning identifies nullclines in oscillatory dynamical systems </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Prokop,+B">Bartosz Prokop</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Billen,+J">Jimmy Billen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Frolov,+N">Nikita Frolov</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Gelens,+L">Lendert Gelens</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 7 pages, 4 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Dynamical Systems (math.DS); Adaptation and Self-Organizing Systems (nlin.AO); Computational Physics (physics.comp-ph) </div> </div> </dd> <dt> <a name='item17'>[17]</a> <a href ="/abs/2503.16233" title="Abstract" id="2503.16233"> arXiv:2503.16233 </a> [<a href="/pdf/2503.16233" title="Download PDF" id="pdf-2503.16233" aria-labelledby="pdf-2503.16233">pdf</a>, <a href="https://arxiv.org/html/2503.16233v1" title="View HTML" id="html-2503.16233" aria-labelledby="html-2503.16233" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16233" title="Other formats" id="oth-2503.16233" aria-labelledby="oth-2503.16233">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Empirical Analysis of Privacy-Fairness-Accuracy Trade-offs in Federated Learning: A Step Towards Responsible AI </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Wasif,+D">Dawood Wasif</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+D">Dian Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Madabushi,+S">Sindhuja Madabushi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Alluru,+N">Nithin Alluru</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Moore,+T+J">Terrence J. Moore</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Cho,+J">Jin-Hee Cho</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Submitted to IJCAI 2025 (under review) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Cryptography and Security (cs.CR); Distributed, Parallel, and Cluster Computing (cs.DC); Emerging Technologies (cs.ET) </div> </div> </dd> <dt> <a name='item18'>[18]</a> <a href ="/abs/2503.16219" title="Abstract" id="2503.16219"> arXiv:2503.16219 </a> [<a href="/pdf/2503.16219" title="Download PDF" id="pdf-2503.16219" aria-labelledby="pdf-2503.16219">pdf</a>, <a href="https://arxiv.org/html/2503.16219v1" title="View HTML" id="html-2503.16219" aria-labelledby="html-2503.16219" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16219" title="Other formats" id="oth-2503.16219" aria-labelledby="oth-2503.16219">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Reinforcement Learning for Reasoning in Small LLMs: What Works and What Doesn't </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Dang,+Q">Quy-Anh Dang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ngo,+C">Chris Ngo</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Computation and Language (cs.CL) </div> </div> </dd> <dt> <a name='item19'>[19]</a> <a href ="/abs/2503.16207" title="Abstract" id="2503.16207"> arXiv:2503.16207 </a> [<a href="/pdf/2503.16207" title="Download PDF" id="pdf-2503.16207" aria-labelledby="pdf-2503.16207">pdf</a>, <a href="https://arxiv.org/html/2503.16207v1" title="View HTML" id="html-2503.16207" aria-labelledby="html-2503.16207" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16207" title="Other formats" id="oth-2503.16207" aria-labelledby="oth-2503.16207">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Neural Variable-Order Fractional Differential Equation Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Cui,+W">Wenjun Cui</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kang,+Q">Qiyu Kang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+X">Xuhao Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhao,+K">Kai Zhao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tay,+W+P">Wee Peng Tay</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Deng,+W">Weihua Deng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+Y">Yidong Li</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> AAAI 2025 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item20'>[20]</a> <a href ="/abs/2503.16199" title="Abstract" id="2503.16199"> arXiv:2503.16199 </a> [<a href="/pdf/2503.16199" title="Download PDF" id="pdf-2503.16199" aria-labelledby="pdf-2503.16199">pdf</a>, <a href="https://arxiv.org/html/2503.16199v1" title="View HTML" id="html-2503.16199" aria-labelledby="html-2503.16199" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16199" title="Other formats" id="oth-2503.16199" aria-labelledby="oth-2503.16199">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Deferring Concept Bottleneck Models: Learning to Defer Interventions to Inaccurate Experts </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Pugnana,+A">Andrea Pugnana</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Massidda,+R">Riccardo Massidda</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Giannini,+F">Francesco Giannini</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Barbiero,+P">Pietro Barbiero</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zarlenga,+M+E">Mateo Espinosa Zarlenga</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Pellungrini,+R">Roberto Pellungrini</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Dominici,+G">Gabriele Dominici</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Giannotti,+F">Fosca Giannotti</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bacciu,+D">Davide Bacciu</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item21'>[21]</a> <a href ="/abs/2503.16192" title="Abstract" id="2503.16192"> arXiv:2503.16192 </a> [<a href="/pdf/2503.16192" title="Download PDF" id="pdf-2503.16192" aria-labelledby="pdf-2503.16192">pdf</a>, <a href="https://arxiv.org/html/2503.16192v1" title="View HTML" id="html-2503.16192" aria-labelledby="html-2503.16192" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16192" title="Other formats" id="oth-2503.16192" aria-labelledby="oth-2503.16192">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Nonparametric Bellman Mappings for Value Iteration in Distributed Reinforcement Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Akiyama,+Y">Yuki Akiyama</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Slavakis,+K">Konstantinos Slavakis</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Signal Processing (eess.SP) </div> </div> </dd> <dt> <a name='item22'>[22]</a> <a href ="/abs/2503.16187" title="Abstract" id="2503.16187"> arXiv:2503.16187 </a> [<a href="/pdf/2503.16187" title="Download PDF" id="pdf-2503.16187" aria-labelledby="pdf-2503.16187">pdf</a>, <a href="https://arxiv.org/html/2503.16187v1" title="View HTML" id="html-2503.16187" aria-labelledby="html-2503.16187" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16187" title="Other formats" id="oth-2503.16187" aria-labelledby="oth-2503.16187">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Manifold learning in metric spaces </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Xu,+L">Liane Xu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Singer,+A">Amit Singer</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item23'>[23]</a> <a href ="/abs/2503.16183" title="Abstract" id="2503.16183"> arXiv:2503.16183 </a> [<a href="/pdf/2503.16183" title="Download PDF" id="pdf-2503.16183" aria-labelledby="pdf-2503.16183">pdf</a>, <a href="https://arxiv.org/html/2503.16183v1" title="View HTML" id="html-2503.16183" aria-labelledby="html-2503.16183" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16183" title="Other formats" id="oth-2503.16183" aria-labelledby="oth-2503.16183">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Variance-Aware Noisy Training: Hardening DNNs against Unstable Analog Computations </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+X">Xiao Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Borras,+H">Hendrik Borras</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Klein,+B">Bernhard Klein</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Fr%C3%B6ning,+H">Holger Fr枚ning</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item24'>[24]</a> <a href ="/abs/2503.16159" title="Abstract" id="2503.16159"> arXiv:2503.16159 </a> [<a href="/pdf/2503.16159" title="Download PDF" id="pdf-2503.16159" aria-labelledby="pdf-2503.16159">pdf</a>, <a href="https://arxiv.org/html/2503.16159v1" title="View HTML" id="html-2503.16159" aria-labelledby="html-2503.16159" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16159" title="Other formats" id="oth-2503.16159" aria-labelledby="oth-2503.16159">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Neural Combinatorial Optimization for Real-World Routing </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Son,+J">Jiwoo Son</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhao,+Z">Zhikai Zhao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Berto,+F">Federico Berto</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hua,+C">Chuanbo Hua</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kwon,+C">Changhyun Kwon</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Park,+J">Jinkyoo Park</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI) </div> </div> </dd> <dt> <a name='item25'>[25]</a> <a href ="/abs/2503.16117" title="Abstract" id="2503.16117"> arXiv:2503.16117 </a> [<a href="/pdf/2503.16117" title="Download PDF" id="pdf-2503.16117" aria-labelledby="pdf-2503.16117">pdf</a>, <a href="/format/2503.16117" title="Other formats" id="oth-2503.16117" aria-labelledby="oth-2503.16117">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Improving Discriminator Guidance in Diffusion Models </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Verine,+A">Alexandre Verine</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Inane,+M">Mehdi Inane</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bronnec,+F+L">Florian Le Bronnec</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Negrevergne,+B">Benjamin Negrevergne</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chevaleyre,+Y">Yann Chevaleyre</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item26'>[26]</a> <a href ="/abs/2503.16107" title="Abstract" id="2503.16107"> arXiv:2503.16107 </a> [<a href="/pdf/2503.16107" title="Download PDF" id="pdf-2503.16107" aria-labelledby="pdf-2503.16107">pdf</a>, <a href="/format/2503.16107" title="Other formats" id="oth-2503.16107" aria-labelledby="oth-2503.16107">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Learn to Bid as a Price-Maker Wind Power Producer </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Singhal,+S">Shobhit Singhal</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Fochesato,+M">Marta Fochesato</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Aolaritei,+L">Liviu Aolaritei</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=D%C3%B6rfler,+F">Florian D枚rfler</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Systems and Control (eess.SY) </div> </div> </dd> <dt> <a name='item27'>[27]</a> <a href ="/abs/2503.16091" title="Abstract" id="2503.16091"> arXiv:2503.16091 </a> [<a href="/pdf/2503.16091" title="Download PDF" id="pdf-2503.16091" aria-labelledby="pdf-2503.16091">pdf</a>, <a href="https://arxiv.org/html/2503.16091v1" title="View HTML" id="html-2503.16091" aria-labelledby="html-2503.16091" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16091" title="Other formats" id="oth-2503.16091" aria-labelledby="oth-2503.16091">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> AIMI: Leveraging Future Knowledge and Personalization in Sparse Event Forecasting for Treatment Adherence </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Mamun,+A">Abdullah Mamun</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Cook,+D+J">Diane J. Cook</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ghasemzadeh,+H">Hassan Ghasemzadeh</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 15 pages, 5 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI) </div> </div> </dd> <dt> <a name='item28'>[28]</a> <a href ="/abs/2503.16081" title="Abstract" id="2503.16081"> arXiv:2503.16081 </a> [<a href="/pdf/2503.16081" title="Download PDF" id="pdf-2503.16081" aria-labelledby="pdf-2503.16081">pdf</a>, <a href="https://arxiv.org/html/2503.16081v1" title="View HTML" id="html-2503.16081" aria-labelledby="html-2503.16081" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16081" title="Other formats" id="oth-2503.16081" aria-labelledby="oth-2503.16081">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> OThink-MR1: Stimulating multimodal generalized reasoning capabilities through dynamic reinforcement learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+Z">Zhiyuan Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+Y">Yuting Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+F">Feng Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+C">Changwang Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Sun,+Y">Ying Sun</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+J">Jun Wang</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Information Retrieval (cs.IR) </div> </div> </dd> <dt> <a name='item29'>[29]</a> <a href ="/abs/2503.16072" title="Abstract" id="2503.16072"> arXiv:2503.16072 </a> [<a href="/pdf/2503.16072" title="Download PDF" id="pdf-2503.16072" aria-labelledby="pdf-2503.16072">pdf</a>, <a href="https://arxiv.org/html/2503.16072v1" title="View HTML" id="html-2503.16072" aria-labelledby="html-2503.16072" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.16072" title="Other formats" id="oth-2503.16072" aria-labelledby="oth-2503.16072">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Redefining Toxicity: An Objective and Context-Aware Approach for Stress-Level-Based Detection </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Berezin,+S">Sergey Berezin</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Farahbakhsh,+R">Reza Farahbakhsh</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Crespi,+N">Noel Crespi</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI); Computation and Language (cs.CL) </div> </div> </dd> <dt> <a name='item30'>[30]</a> <a href ="/abs/2503.15972" title="Abstract" id="2503.15972"> arXiv:2503.15972 </a> [<a href="/pdf/2503.15972" title="Download PDF" id="pdf-2503.15972" aria-labelledby="pdf-2503.15972">pdf</a>, <a href="https://arxiv.org/html/2503.15972v1" title="View HTML" id="html-2503.15972" aria-labelledby="html-2503.15972" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15972" title="Other formats" id="oth-2503.15972" aria-labelledby="oth-2503.15972">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> TVineSynth: A Truncated C-Vine Copula Generator of Synthetic Tabular Data to Balance Privacy and Utility </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Griesbauer,+E">Elisabeth Griesbauer</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Czado,+C">Claudia Czado</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Frigessi,+A">Arnoldo Frigessi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Haff,+I+H">Ingrid Hob忙k Haff</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted at the 28th International Conference on Artificial Intelligence and Statistics (AISTATS 2025) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item31'>[31]</a> <a href ="/abs/2503.15962" title="Abstract" id="2503.15962"> arXiv:2503.15962 </a> [<a href="/pdf/2503.15962" title="Download PDF" id="pdf-2503.15962" aria-labelledby="pdf-2503.15962">pdf</a>, <a href="/format/2503.15962" title="Other formats" id="oth-2503.15962" aria-labelledby="oth-2503.15962">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Information maximization for a broad variety of multi-armed bandit games </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Barbier-Chebbah,+A">Alex Barbier-Chebbah</a> (EPIMETHEE), <a href="https://arxiv.org/search/cs?searchtype=author&query=Vestergaard,+C+L">Christian L. Vestergaard</a> (EPIMETHEE), <a href="https://arxiv.org/search/cs?searchtype=author&query=Masson,+J">Jean-Baptiste Masson</a> (EPIMETHEE)</div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Statistical Mechanics (cond-mat.stat-mech); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item32'>[32]</a> <a href ="/abs/2503.15946" title="Abstract" id="2503.15946"> arXiv:2503.15946 </a> [<a href="/pdf/2503.15946" title="Download PDF" id="pdf-2503.15946" aria-labelledby="pdf-2503.15946">pdf</a>, <a href="https://arxiv.org/html/2503.15946v1" title="View HTML" id="html-2503.15946" aria-labelledby="html-2503.15946" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15946" title="Other formats" id="oth-2503.15946" aria-labelledby="oth-2503.15946">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Multivariate Time Series Anomaly Detection in Industry 5.0 </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Colombi,+L">Lorenzo Colombi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Vespa,+M">Michela Vespa</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Belletti,+N">Nicolas Belletti</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Brina,+M">Matteo Brina</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Dahdal,+S">Simon Dahdal</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tabanelli,+F">Filippo Tabanelli</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bellodi,+E">Elena Bellodi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tortonesi,+M">Mauro Tortonesi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Stefanelli,+C">Cesare Stefanelli</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Vignoli,+M">Massimiliano Vignoli</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item33'>[33]</a> <a href ="/abs/2503.15928" title="Abstract" id="2503.15928"> arXiv:2503.15928 </a> [<a href="/pdf/2503.15928" title="Download PDF" id="pdf-2503.15928" aria-labelledby="pdf-2503.15928">pdf</a>, <a href="https://arxiv.org/html/2503.15928v1" title="View HTML" id="html-2503.15928" aria-labelledby="html-2503.15928" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15928" title="Other formats" id="oth-2503.15928" aria-labelledby="oth-2503.15928">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Sample-Efficient Bayesian Transfer Learning for Online Machine Parameter Optimization </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Wagner,+P">Philipp Wagner</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Nagel,+T">Tobias Nagel</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Leube,+P">Philipp Leube</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Huber,+M+F">Marco F. Huber</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted in IEEE Conference on Artificial Intelligence, 2025 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item34'>[34]</a> <a href ="/abs/2503.15918" title="Abstract" id="2503.15918"> arXiv:2503.15918 </a> [<a href="/pdf/2503.15918" title="Download PDF" id="pdf-2503.15918" aria-labelledby="pdf-2503.15918">pdf</a>, <a href="https://arxiv.org/html/2503.15918v1" title="View HTML" id="html-2503.15918" aria-labelledby="html-2503.15918" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15918" title="Other formats" id="oth-2503.15918" aria-labelledby="oth-2503.15918">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Denoising-based Contractive Imitation Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Shen,+M">Macheng Shen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Peng,+J">Jishen Peng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Huang,+Z">Zefang Huang</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI) </div> </div> </dd> <dt> <a name='item35'>[35]</a> <a href ="/abs/2503.15902" title="Abstract" id="2503.15902"> arXiv:2503.15902 </a> [<a href="/pdf/2503.15902" title="Download PDF" id="pdf-2503.15902" aria-labelledby="pdf-2503.15902">pdf</a>, <a href="https://arxiv.org/html/2503.15902v1" title="View HTML" id="html-2503.15902" aria-labelledby="html-2503.15902" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15902" title="Other formats" id="oth-2503.15902" aria-labelledby="oth-2503.15902">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> On the Limits of Applying Graph Transformers for Brain Connectome Classification </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Lara-Rangel,+J">Jose Lara-Rangel</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Heinbaugh,+C">Clare Heinbaugh</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item36'>[36]</a> <a href ="/abs/2503.15890" title="Abstract" id="2503.15890"> arXiv:2503.15890 </a> [<a href="/pdf/2503.15890" title="Download PDF" id="pdf-2503.15890" aria-labelledby="pdf-2503.15890">pdf</a>, <a href="https://arxiv.org/html/2503.15890v1" title="View HTML" id="html-2503.15890" aria-labelledby="html-2503.15890" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15890" title="Other formats" id="oth-2503.15890" aria-labelledby="oth-2503.15890">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Time After Time: Deep-Q Effect Estimation for Interventions on When and What to do </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Wald,+Y">Yoav Wald</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Goldstein,+M">Mark Goldstein</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Efroni,+Y">Yonathan Efroni</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=van+Amsterdam,+W+A">Wouter A.C. van Amsterdam</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ranganath,+R">Rajesh Ranganath</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI) </div> </div> </dd> <dt> <a name='item37'>[37]</a> <a href ="/abs/2503.15889" title="Abstract" id="2503.15889"> arXiv:2503.15889 </a> [<a href="/pdf/2503.15889" title="Download PDF" id="pdf-2503.15889" aria-labelledby="pdf-2503.15889">pdf</a>, <a href="https://arxiv.org/html/2503.15889v1" title="View HTML" id="html-2503.15889" aria-labelledby="html-2503.15889" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15889" title="Other formats" id="oth-2503.15889" aria-labelledby="oth-2503.15889">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> LeanTTA: A Backpropagation-Free and Stateless Approach to Quantized Test-Time Adaptation on Edge Devices </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Dong,+C">Cynthia Dong</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jia,+H">Hong Jia</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kwon,+Y+D">Young D. Kwon</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Rizos,+G">Georgios Rizos</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Mascolo,+C">Cecilia Mascolo</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 8 pages, 5 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI) </div> </div> </dd> <dt> <a name='item38'>[38]</a> <a href ="/abs/2503.15880" title="Abstract" id="2503.15880"> arXiv:2503.15880 </a> [<a href="/pdf/2503.15880" title="Download PDF" id="pdf-2503.15880" aria-labelledby="pdf-2503.15880">pdf</a>, <a href="https://arxiv.org/html/2503.15880v1" title="View HTML" id="html-2503.15880" aria-labelledby="html-2503.15880" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15880" title="Other formats" id="oth-2503.15880" aria-labelledby="oth-2503.15880">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> InCo-DPO: Balancing Distribution Shift and Data Quality for Enhanced Preference Optimization </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+Y">Yunan Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+J">Jijie Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+B">Bo-Wen Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+L">Liangdong Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+G">Guang Liu</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Computation and Language (cs.CL) </div> </div> </dd> <dt> <a name='item39'>[39]</a> <a href ="/abs/2503.15870" title="Abstract" id="2503.15870"> arXiv:2503.15870 </a> [<a href="/pdf/2503.15870" title="Download PDF" id="pdf-2503.15870" aria-labelledby="pdf-2503.15870">pdf</a>, <a href="https://arxiv.org/html/2503.15870v1" title="View HTML" id="html-2503.15870" aria-labelledby="html-2503.15870" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15870" title="Other formats" id="oth-2503.15870" aria-labelledby="oth-2503.15870">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> FedSAF: A Federated Learning Framework for Enhanced Gastric Cancer Detection and Privacy Preservation </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Miao,+Y">Yuxin Miao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yang,+X">Xinyuan Yang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Fan,+H">Hongda Fan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+Y">Yichun Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hong,+Y">Yishu Hong</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Guo,+X">Xiechen Guo</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Braytee,+A">Ali Braytee</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Huang,+W">Weidong Huang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Anaissi,+A">Ali Anaissi</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item40'>[40]</a> <a href ="/abs/2503.15865" title="Abstract" id="2503.15865"> arXiv:2503.15865 </a> [<a href="/pdf/2503.15865" title="Download PDF" id="pdf-2503.15865" aria-labelledby="pdf-2503.15865">pdf</a>, <a href="/format/2503.15865" title="Other formats" id="oth-2503.15865" aria-labelledby="oth-2503.15865">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Active management of battery degradation in wireless sensor network using deep reinforcement learning for group battery replacement </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Jeonga,+J">Jong-Hyun Jeonga</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jo,+H">Hongki Jo</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhou,+Q">Qiang Zhou</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Nishat,+T+A+H">Tahsin Afroz Hoque Nishat</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wu,+L">Lang Wu</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI) </div> </div> </dd> <dt> <a name='item41'>[41]</a> <a href ="/abs/2503.15853" title="Abstract" id="2503.15853"> arXiv:2503.15853 </a> [<a href="/pdf/2503.15853" title="Download PDF" id="pdf-2503.15853" aria-labelledby="pdf-2503.15853">pdf</a>, <a href="https://arxiv.org/html/2503.15853v1" title="View HTML" id="html-2503.15853" aria-labelledby="html-2503.15853" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15853" title="Other formats" id="oth-2503.15853" aria-labelledby="oth-2503.15853">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Network Embedding Exploration Tool (NEExT) </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Dehghan,+A">Ashkan Dehghan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Pra%C5%82at,+P">Pawe艂 Pra艂at</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Th%C3%A9berge,+F">Fran莽ois Th茅berge</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 24 pages, 10 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item42'>[42]</a> <a href ="/abs/2503.15845" title="Abstract" id="2503.15845"> arXiv:2503.15845 </a> [<a href="/pdf/2503.15845" title="Download PDF" id="pdf-2503.15845" aria-labelledby="pdf-2503.15845">pdf</a>, <a href="https://arxiv.org/html/2503.15845v1" title="View HTML" id="html-2503.15845" aria-labelledby="html-2503.15845" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15845" title="Other formats" id="oth-2503.15845" aria-labelledby="oth-2503.15845">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Network-wide Freeway Traffic Estimation Using Sparse Sensor Data: A Dirichlet Graph Auto-Encoder Approach </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Zhou,+Q">Qishen Zhou</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+Y">Yifan Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Makridis,+M+A">Michail A. Makridis</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kouvelas,+A">Anastasios Kouvelas</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+Y">Yibing Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hu,+S">Simon Hu</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> This work has been submitted to the IEEE for possible publication </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item43'>[43]</a> <a href ="/abs/2503.15842" title="Abstract" id="2503.15842"> arXiv:2503.15842 </a> [<a href="/pdf/2503.15842" title="Download PDF" id="pdf-2503.15842" aria-labelledby="pdf-2503.15842">pdf</a>, <a href="https://arxiv.org/html/2503.15842v1" title="View HTML" id="html-2503.15842" aria-labelledby="html-2503.15842" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15842" title="Other formats" id="oth-2503.15842" aria-labelledby="oth-2503.15842">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> FedAWA: Adaptive Optimization of Aggregation Weights in Federated Learning Using Client Vectors </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Shi,+C">Changlong Shi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhao,+H">He Zhao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+B">Bingjie Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhou,+M">Mingyuan Zhou</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Guo,+D">Dandan Guo</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chang,+Y">Yi Chang</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted in CVPR 2025 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item44'>[44]</a> <a href ="/abs/2503.15804" title="Abstract" id="2503.15804"> arXiv:2503.15804 </a> [<a href="/pdf/2503.15804" title="Download PDF" id="pdf-2503.15804" aria-labelledby="pdf-2503.15804">pdf</a>, <a href="https://arxiv.org/html/2503.15804v1" title="View HTML" id="html-2503.15804" aria-labelledby="html-2503.15804" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15804" title="Other formats" id="oth-2503.15804" aria-labelledby="oth-2503.15804">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Communication Efficient Federated Learning with Linear Convergence on Heterogeneous Data </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+J">Jie Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+Y">Yongqiang Wang</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Optimization and Control (math.OC) </div> </div> </dd> <dt> <a name='item45'>[45]</a> <a href ="/abs/2503.15801" title="Abstract" id="2503.15801"> arXiv:2503.15801 </a> [<a href="/pdf/2503.15801" title="Download PDF" id="pdf-2503.15801" aria-labelledby="pdf-2503.15801">pdf</a>, <a href="https://arxiv.org/html/2503.15801v1" title="View HTML" id="html-2503.15801" aria-labelledby="html-2503.15801" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15801" title="Other formats" id="oth-2503.15801" aria-labelledby="oth-2503.15801">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Disentangling Uncertainties by Learning Compressed Data Representation </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=An,+Z">Zhiyu An</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Hou,+Z">Zhibo Hou</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Du,+W">Wan Du</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted by the 7th Annual Learning for Dynamics & Control Conference (L4DC) 2025 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item46'>[46]</a> <a href ="/abs/2503.15798" title="Abstract" id="2503.15798"> arXiv:2503.15798 </a> [<a href="/pdf/2503.15798" title="Download PDF" id="pdf-2503.15798" aria-labelledby="pdf-2503.15798">pdf</a>, <a href="https://arxiv.org/html/2503.15798v1" title="View HTML" id="html-2503.15798" aria-labelledby="html-2503.15798" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15798" title="Other formats" id="oth-2503.15798" aria-labelledby="oth-2503.15798">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Mixture of Lookup Experts </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Jie,+S">Shibo Jie</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tang,+Y">Yehui Tang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Han,+K">Kai Han</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+Y">Yitong Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tang,+D">Duyu Tang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Deng,+Z">Zhi-Hong Deng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+Y">Yunhe Wang</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Computation and Language (cs.CL) </div> </div> </dd> <dt> <a name='item47'>[47]</a> <a href ="/abs/2503.15796" title="Abstract" id="2503.15796"> arXiv:2503.15796 </a> [<a href="/pdf/2503.15796" title="Download PDF" id="pdf-2503.15796" aria-labelledby="pdf-2503.15796">pdf</a>, <a href="https://arxiv.org/html/2503.15796v1" title="View HTML" id="html-2503.15796" aria-labelledby="html-2503.15796" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15796" title="Other formats" id="oth-2503.15796" aria-labelledby="oth-2503.15796">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Blend the Separated: Mixture of Synergistic Experts for Data-Scarcity Drug-Target Interaction Prediction </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Zhai,+X">Xinlong Zhai</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+C">Chunchen Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+R">Ruijia Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kang,+J">Jiazheng Kang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+S">Shujie Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+B">Boyu Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ma,+T">Tengfei Ma</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhou,+Z">Zikai Zhou</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yang,+C">Cheng Yang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Shi,+C">Chuan Shi</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI) </div> </div> </dd> <dt> <a name='item48'>[48]</a> <a href ="/abs/2503.15793" title="Abstract" id="2503.15793"> arXiv:2503.15793 </a> [<a href="/pdf/2503.15793" title="Download PDF" id="pdf-2503.15793" aria-labelledby="pdf-2503.15793">pdf</a>, <a href="https://arxiv.org/html/2503.15793v1" title="View HTML" id="html-2503.15793" aria-labelledby="html-2503.15793" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15793" title="Other formats" id="oth-2503.15793" aria-labelledby="oth-2503.15793">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> DNA Bench: When Silence is Smarter -- Benchmarking Over-Reasoning in Reasoning LLMs </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Hashemi,+M">Masoud Hashemi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bamgbose,+O">Oluwanifemi Bamgbose</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Madhusudhan,+S+T">Sathwik Tejaswi Madhusudhan</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Nair,+J+S">Jishnu Sethumadhavan Nair</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tiwari,+A">Aman Tiwari</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yadav,+V">Vikas Yadav</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> <dt> <a name='item49'>[49]</a> <a href ="/abs/2503.15779" title="Abstract" id="2503.15779"> arXiv:2503.15779 </a> [<a href="/pdf/2503.15779" title="Download PDF" id="pdf-2503.15779" aria-labelledby="pdf-2503.15779">pdf</a>, <a href="https://arxiv.org/html/2503.15779v1" title="View HTML" id="html-2503.15779" aria-labelledby="html-2503.15779" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15779" title="Other formats" id="oth-2503.15779" aria-labelledby="oth-2503.15779">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> MobiFuse: Learning Universal Human Mobility Patterns through Cross-domain Data Fusion </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Ma,+H">Haoxuan Ma</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liao,+X">Xishun Liao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+Y">Yifan Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jiang,+Q">Qinhua Jiang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Stanford,+C">Chris Stanford</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Cao,+S">Shangqing Cao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ma,+J">Jiaqi Ma</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span>; Artificial Intelligence (cs.AI) </div> </div> </dd> <dt> <a name='item50'>[50]</a> <a href ="/abs/2503.15777" title="Abstract" id="2503.15777"> arXiv:2503.15777 </a> [<a href="/pdf/2503.15777" title="Download PDF" id="pdf-2503.15777" aria-labelledby="pdf-2503.15777">pdf</a>, <a href="https://arxiv.org/html/2503.15777v1" title="View HTML" id="html-2503.15777" aria-labelledby="html-2503.15777" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.15777" title="Other formats" id="oth-2503.15777" aria-labelledby="oth-2503.15777">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Line Space Clustering (LSC): Feature-Based Clustering using K-medians and Dynamic Time Warping for Versatility </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Chulev,+J">Joanikij Chulev</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Mladenovska,+A">Angela Mladenovska</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 8 pages, 5 figures, 3 tables </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (cs.LG)</span> </div> </div> </dd> </dl> <div class='paging'>Total of 807 entries : <span>1-50</span> <a href=/list/cs.LG/recent?skip=50&show=50>51-100</a> <a href=/list/cs.LG/recent?skip=100&show=50>101-150</a> <a href=/list/cs.LG/recent?skip=150&show=50>151-200</a> <span>...</span> <a href=/list/cs.LG/recent?skip=800&show=50>801-807</a> </div> <div class='morefewer'>Showing up to 50 entries per page: <a href=/list/cs.LG/recent?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/cs.LG/recent?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/cs.LG/recent?skip=0&show=2000 rel="nofollow"> all</a> </div> </div> </div> </div> </main> <footer style="clear: both;"> <div class="columns is-desktop" role="navigation" aria-label="Secondary" style="margin: -0.75em -0.75em 0.75em -0.75em"> <!-- Macro-Column 1 --> <div class="column" style="padding: 0;"> <div class="columns"> <div class="column"> <ul style="list-style: none; 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