University of Michigan（密歇根大学安娜堡分校）

GNN-based Path-aware multi-view Circuit Learning for Technology Mapping

基于GNN的路径感知多视图电路学习用于技术映射

Wentao Jiang, Jingxin Wang, Zhang Hu, Zhengyuan Shi, Chengyu Ma, Qiang Xu, Weikang Qian, Zhufei Chu

机构 * Faculty of Electrical Engineering and Computer Science, NingBo University（电子工程与计算机科学学院，宁波大学） ； University of Michigan-Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University（密歇根大学-上海交通大学联合研究所，上海交通大学） ； Department of Computer Science and Engineering, The Chinese University of Hong Kong（中国香港中文大学计算机科学与工程系） 纠错

AI总结 GPA通过融合多视图电路结构学习，提升技术映射中延迟预测的准确性，实现更高效的映射决策。

Comments 7pages, 4figures

Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration

人工智能/机器学习在Rubin LSST暗能量科学合作中的机遇

LSST Dark Energy Science Collaboration, Eric Aubourg, Camille Avestruz, Matthew R. Becker, Biswajit Biswas, Rahul Biswas, Boris Bolliet, Adam S. Bolton, Clecio R. Bom, Raphaël Bonnet-Guerrini, Alexandre Boucaud, Jean-Eric Campagne, Chihway Chang, Aleksandra Ćiprijanović, Johann Cohen-Tanugi, Michael W. Coughlin, John Franklin Crenshaw, Juan C. Cuevas-Tello, Juan de Vicente, Seth W. Digel, Steven Dillmann, Mariano Javier de León Dominguez Romero, Alex Drlica-Wagner, Sydney Erickson, Alexander T. Gagliano, Christos Georgiou, Aritra Ghosh, Matthew Grayling, Kirill A. Grishin, Alan Heavens, Lindsay R. House, Mustapha Ishak, Wassim Kabalan, Arun Kannawadi, François Lanusse, C. Danielle Leonard, Pierre-François Léget, Michelle Lochner, Yao-Yuan Mao, Peter Melchior, Grant Merz, Martin Millon, Anais Möller, Gautham Narayan, Yuuki Omori, Hiranya Peiris, Laurence Perreault-Levasseur, Andrés A. Plazas Malagón, Nesar Ramachandra, Benjamin Remy, Cécile Roucelle, Jaime Ruiz-Zapatero, Stefan Schuldt, Ignacio Sevilla-Noarbe, Ved G. Shah, Tjitske Starkenburg, Stephen Thorp, Laura Toribio San Cipriano, Tilman Tröster, Roberto Trotta, Padma Venkatraman, Amanda Wasserman, Tim White, Justine Zeghal, Tianqing Zhang, Yuanyuan Zhang

机构 * Université Paris Cité, CNRS, CEA, Astroparticule et Cosmologie, F-75013 Paris, France ； Department of Physics, University of Michigan, Ann Arbor, MI 48109, USA ； Leinweber Institute of Theoretical Physics, University of Michigan, Ann Arbor, MI 48109, USA ； Argonne National Laboratory, 9700 South Cass Avenue, Lemont, IL 60439, USA ； Cavendish Astrophysics, University of Cambridge, Madingley Road, Cambridge CB3 0HA, UK ； Kavli Institute for Cosmology, University of Cambridge, Madingley Road, Cambridge CB3 0HA, UK ； SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA ； Department of Computer Science, University of Milan, Milan, Italy ； Université Paris Cité, CNRS, Astroparticule et Cosmologie, F-75013 Paris, France ； Université Paris-Saclay, CNRS/IN2P3, IJCLab, 91405 Orsay, France ； Department of Astronomy ； Astrophysics, University of Chicago, Chicago, IL 60637, USA ； Kavli Institute for Cosmological Physics, University of Chicago, Chicago, IL 60637, USA ； NSF-Simons AI Institute for the Sky (SkAI), 172 E. Chestnut St., Chicago, IL 60611, USA ； Fermi National Accelerator Laboratory, P.O. Box 500, Batavia, IL 60510, USA ； Universit\'e Clermont-Auvergne, CNRS, LPCA, 63000 Clermont-Ferrand, France ； Kavli Institute for Particle Astrophysics ； Cosmology, Stanford University, Stanford, CA 94305, USA ； Department of Physics, Stanford University, 382 Via Pueblo Mall, Stanford, CA 94305, USA ； Engineering Faculty, Universidad Autonoma de San Luis Potosi, Zona Universitaria, San Luis Potosi, 78290, Mexico ； Stanford Artificial Intelligence Laboratory, Stanford University, Stanford, CA 94305, USA ； Kavli Institute of Cosmological Physics, University of Chicago, Chicago, IL 60637, USA ； The NSF AI Institute for Artificial Intelligence ； Center for Astrophysics Harvard \& Smithsonian, 60 Garden Street, Cambridge, MA 02138, USA ； Department of Physics ； Kavli Institute for Astrophysics ； Space Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA ； Institut de Física d'Altes Energies (IFAE), The Barcelona Institute of Science ； Institute of Astronomy ； Kavli Institute for Cosmology, University of Cambridge, Madingley Road, Cambridge, CB3 0HA, UK ； Imperial Centre for Inference ； Cosmology (ICIC), Imperial College London, Blackett Laboratory, Prince Consort Road, London SW7 2AZ, UK ； Data Science Institute, The University of Chicago, Chicago, IL 60615, USA ； Department of Physics, The University of Texas at Dallas, Richardson, TX 75080, USA ； Department of Physics, Duke University, Durham, NC 27708, USA ； Université Paris-Saclay, Université Paris Cité, CEA, CNRS, AIM, F-91191 Gif-sur-Yvette, France ； School of Mathematics, Statistics ； Physics, Newcastle University, Newcastle upon Tyne, NE1 7RU, United Kingdom ； Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08544, USA ； Astronomy, University of the Western Cape, Bellville, Cape Town, 7535, South Africa ； Astronomy, University of Utah, Salt Lake City, UT 84112, USA ； Department of Astrophysical Sciences, Princeton University, Peyton Hall, Princeton, NJ 08544, USA ； Department of Astronomy, University of Illinois Urbana Champaign, 1002 W. Green St., Urbana, IL, 61801, USA ； Institute for Particle Physics ； Astrophysics, ETH Zürich, Wolfgang-Pauli-Strasse 27, CH-8093 Zurich, Switzerland ； Swinburne University of Technology, Hawthorn, Victoria 3122, Australia ； Ciela - Montr\'eal Institute for Astrophysical Data Analysis ； Mila - Quebec Artificial Intelligence Institute, Montréal, QC H2S 3H1, Canada ； Advanced Research Computing Centre, University College London, 90 High Holborn, London WC1V 6LJ, UK ； Finnish Centre for Astronomy with ESO (FINCA), University of Turku, FI-20014 Turku, Finland ； Department of Physics, P.O. Box 64, University of Helsinki, FI-00014 Helsinki, Finland ； Astronomy, Northwestern University, Evanston, IL, USA ； Center for Interdisciplinary Exploration ； Research in Astrophysics, Northwestern University, Evanston, IL, USA ； Scientific Data Science, International School for Advanced Study, Via Bonomea 265, I-34136 Trieste, Italy ； Department of Statistics, University of Michigan, Ann Arbor, MI 48109, USA ； PITT PACC, University of Pittsburgh, Pittsburgh, PA 15260, USA ； NSF NOIRLab, 950 N. Cherry Ave., Tucson, AZ 85719, USA 纠错

AI总结 本文探讨了AI/ML在LSST暗能量科学合作中的应用机遇，强调了大规模贝叶斯推断、物理指导方法和主动学习等关键方法学优先事项，并讨论了新兴技术在重塑工作流程中的潜力。

Comments 84 pages. This is v1.0 of the DESC's white paper on AI/ML, a collaboration document that is being made public but which is not planned for submission to a journal

Pathways of Thoughts: Multi-Directional Thinking for Long-form Personalized Question Answering

思维路径：多方向思考用于长文本个性化问答

Alireza Salemi, Cheng Li, Mingyang Zhang, Qiaozhu Mei, Zhuowan Li, Spurthi Amba Hombaiah, Weize Kong, Tao Chen, Hamed Zamani, Michael Bendersky

机构 * University of Massachusetts Amherst（马萨诸塞大学阿默斯特分校） ； Google DeepMind（谷歌DeepMind） ； University of Michigan（密歇根大学） 纠错

AI总结 本文提出PoT方法，通过多方向思考生成个性化问答响应，实验证明其在长文本问答任务中表现优异。