机构
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Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai(人工智能与人类健康系,伊坎医学院 Mount Sinai 分校)
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Department of Psychiatry, Icahn School of Medicine at Mount Sinai(精神病学系,伊坎医学院 Mount Sinai 分校)
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Department of Neuroscience, Icahn School of Medicine at Mount Sinai(神经科学系,伊坎医学院 Mount Sinai 分校)
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Berkman Klein Center for Internet & Society, Harvard University(互联网与社会研究中心,哈佛大学)
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IBM Research, T.J. Watson Research Center(IBM 研究,T.J. Watson 研究中心)
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Mental Illness Research, Education and Clinical Center, James J. Peters VA Medical Center(精神疾病研究、教育与临床中心,James J. Peters VA 医疗中心)
CommentsTranslational Psychiatry, in press. This work extends our research series in computational psychiatry (e.g auto annotation in arXiv:2204.05522, topic extraction in arXiv:2204.10189, and diagnosis in arXiv:2210.15603) with the introduction of LLMs to complete the full cycle of interpreting and understanding psychotherapy strategies as a comprehensive analytical framework
ALOPE: Adaptive Layer Optimization for Translation Quality Estimation using Large Language Models
Archchana Sindhujan, Shenbin Qian, Chan Chi Chun Matthew, Constantin Orasan, Diptesh Kanojia
机构
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Institute for People-Centred AI and Centre for Translation Studies, School of Computer Science and Electronic Engineering, University of Surrey(以人为本的人工智能研究所和翻译研究中心,计算机科学与电子工程学院,萨里大学)
A novel language model for predicting serious adverse event results in clinical trials from their prospective registrations
Qixuan Hu, Xumou Zhang, Jinman Kim, Florence Bourgeois, Adam G. Dunn
机构
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School of Computer Science, Faculty of Engineering, University of Sydney(悉尼大学计算机科学学院、工程学院)
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Computational Health Informatics Program, Boston Children’s Hospital(波士顿儿童医院计算健康信息学项目)
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Harvard-MIT Center for Regulatory Science and Department of Pediatrics, Harvard Medical School(哈佛-麻省理工监管科学中心和哈佛医学院儿科部门)
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Sydney School of Public Health, Faculty of Medicine and Health, University of Sydney(悉尼大学公共卫生学院、医学与健康学院)
专题命中
其他安全
:safety(abstract);分类 cs.CL、cs.AI
Comments12 pages, 4 figures. Updated to include Table 2, Supplementary Table 1, and an additional baseline random forest model
EEG-Language Pretraining for Highly Label-Efficient Clinical Phenotyping
Sam Gijsen, Kerstin Ritter
机构
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Charité – Universitätsmedizin Berlin, Department of Psychiatry and Psychotherapy, Berlin, Germany(柏林查理医院医学大学精神病与心理治疗系)
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Hertie Institute for AI in Brain Health, University of Tübingen, Germany(图宾根大学健康人工智能研究所)
机构
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Independent Researcher in AI and Statistics(人工智能与统计学独立研究者)
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Shahrood University of Technology(沙霍罗德大学)
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University of Pittsburgh(匹兹堡大学)
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Duquesne University(杜克森大学)
Observation Interference in Partially Observable Assistance Games
Scott Emmons, Caspar Oesterheld, Vincent Conitzer, Stuart Russell
机构
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Center for Human-Compatible AI, University of California, Berkeley(人类兼容人工智能中心,加州大学伯克利分校)
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Foundations of Cooperative AI Lab, Carnegie Mellon University(协作人工智能实验室,卡内基梅隆大学)
机构
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Department of Mechanical Engineering(机械工程系)
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Rajshahi University of Engineering and Technology(拉贾沙希工程与技术大学)
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Department of Industrial and Production Engineering(工业与生产工程系)
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Shahjalal University of Science and Technology(沙赫jalal科学与技术大学)
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Bangladesh University of Engineering and Technology(孟加拉工程与技术大学)
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Department of Urban and Regional Planning(城市与区域规划系)
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Department of Computer Science Engineering(计算机科学与工程系)
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United International University(联合国际大学)
Constrained Hamiltonian Systems on Observation-Induced Fiber Bundles: Theory of Symmetry and Integrability
Dongzhe Zheng
专题命中
其他安全
:safety(abstract)
CommentsThis paper establishes the complete mathematical theory underlying the practical framework presented in "Learning Dynamics under Environmental Constraints via Measurement-Induced Bundle Structures" (ICML 2025 (Forty-Second International Conference on Machine Learning) Spotlight, top 2.5% of ~12,000 submissions)