arXivDaily arXiv每日学术速递 周一至周五更新

高校专区

Harvard University(哈佛大学)

2026-01-27 至 2026-01-27 共收录 5
2601.18102 2026-01-27 cs.CL

CHiRPE: A Step Towards Real-World Clinical NLP with Clinician-Oriented Model Explanations

CHiRPE:迈向真实世界临床NLP的一步:面向临床医生的模型解释

Stephanie Fong, Zimu Wang, Guilherme C. Oliveira, Xiangyu Zhao, Yiwen Jiang, Jiahe Liu, Beau-Luke Colton, Scott Woods, Martha E. Shenton, Barnaby Nelson, Zongyuan Ge, Dominic Dwyer

机构 * Orygen and The University of Melbourne(Orygen和墨尔本大学) AIM for Health Lab, Monash University(AIM for Health实验室,墨尔本大学) University of Liverpool(利物浦大学) Yale School of Medicine, Yale University(耶鲁医学院,耶鲁大学) Brigham and Women’s Hospital, Harvard Medical School(哈佛医学院布里奇沃特医院)

AI总结 CHiRPE通过临床医生共同开发的新型SHAP解释格式,实现了高准确率的临床风险预测,并展示了临床指导的模型开发在真实世界中的应用潜力。

Comments This paper is accepted at EACL 2026

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2601.17510 2026-01-27 stat.ML cs.AI cs.LG

"Rebuilding" Statistics in the Age of AI: A Town Hall Discussion on Culture, Infrastructure, and Training

在人工智能时代重建统计学:关于文化、基础设施和培训的圆桌讨论

David L. Donoho, Jian Kang, Xihong Lin, Bhramar Mukherjee, Dan Nettleton, Rebecca Nugent, Abel Rodriguez, Eric P. Xing, Tian Zheng, Hongtu Zhu

机构 * Department of Statistics, Stanford University(斯坦福大学统计学系) Department of Biostatistics, University of Michigan, Ann Arbor(密歇根大学安娜堡分校生物统计学系) Harvard T.H. Chan School of Public Health(哈佛大学T.H. Chan公共卫生学院) Department of Statistics, Harvard University(哈佛大学统计学系) Broad Institute(Broad研究所) Yale School of Public Health(耶鲁大学公共卫生学院) Department of Statistics and Data Science, Yale University(耶鲁大学统计学与数据科学系) Department of Statistics, Iowa State University(爱荷华州立大学统计学系) Department of Statistics and Data Science, Carnegie Mellon University(卡内基梅隆大学统计学与数据科学系) Baskin School of Engineering, University of California, Santa Cruz(加州大学圣克鲁兹分校Baskin工程学院) Mohamed bin Zayed University of Artificial Intelligence(Mohamed bin Zayed人工智能大学) School of Computer Science, Carnegie Mellon University(卡内基梅隆大学计算机科学学院) Department of Statistics, Columbia University(哥伦比亚大学统计学系) Department of Biostatistics, University of North Carolina at Chapel Hill(北卡罗来纳大学教堂山分校生物统计学系)

AI总结 本文记录了2024年JSM圆桌讨论,探讨统计学在人工智能时代的发展,聚焦文化、基础设施和培训等关键问题。

Comments 35 pages, 3 figures,

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2510.01733 2026-01-27 hep-ex astro-ph.IM cs.LG

Reducing Simulation Dependence in Neutrino Telescopes with Masked Point Transformers

在中微子望远镜中减少模拟依赖性:基于掩码点变换器的方法

Felix J. Yu, Nicholas Kamp, Carlos A. Argüelles

机构 * Department of Physics \& Laboratory of Particle Physics Cosmology, Harvard University, Cambridge, MA, USA

AI总结 本文提出了一种基于点云变换器和掩码自动编码器的自监督学习方法,用于减少中微子望远镜对模拟数据的依赖,从而提升事件重建和分类的准确性。

Comments 8 pages, 3 figures, presented at the 39th International Cosmic Ray Conference (ICRC2025)

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2509.09071 2026-01-27 cs.AI cs.GT cs.HC

Strategic Tradeoffs Between Humans and AI in Multi-Agent Bargaining

人类与AI在多智能体协商中的战略权衡

Crystal Qian, Kehang Zhu, John Horton, Benjamin S. Manning, Vivian Tsai, James Wexler, Nithum Thain

机构 * Google DeepMind Mountain View CA USA(谷歌DeepMind) Harvard University Cambridge MA USA MIT \& NBER Cambridge MA USA MIT Cambridge MA USA Google DeepMind Harvard University MIT \& NBER MIT

AI总结 本研究通过实证分析比较了人类、前沿LLMs和定制化贝叶斯代理在动态多玩家协商游戏中的表现,揭示了LLMs在复杂多代理互动中与人类行为的差异及性能平局的局限性。

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2505.14932 2026-01-27 cs.AI

FOL-Traces: Verified First-Order Logic Reasoning Traces at Scale

FOL-Traces: 在大规模上验证的首阶逻辑推理轨迹

Isabelle Lee, Sarah Liaw, Dani Yogatama

机构 * USC(美国大学) Harvard University(哈佛大学)

AI总结 FOL-Traces是一个大规模验证的首阶逻辑推理轨迹数据集,用于严格评估结构逻辑推理,通过挑战性任务揭示模型在语法意识和推理过程忠实度上的不足。

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