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University of Oxford(牛津大学)

2026-06-30 至 2026-06-30 共收录 8
2606.30304 2026-06-30 cs.DL cs.AI cs.IR

Research Entity Extraction and Topic Detection from UKRI Grant Proposals

从UKRI资助提案中提取研究实体和检测主题

Xingran Ruan, Angelo Salatino, Rosa Filgueira, Kara Moraw, Alexandru Marcoci, Gemma Derrick, Sarah Callaghan

机构 * EPCC, University of Edinburgh, UK(埃克塞特大学埃平中心,英国) Knowledge Media Institute, The Open University, UK(开放大学知识媒体研究所,英国) Institute for Technology and Humanity, University of Cambridge, UK(剑桥大学技术与人类研究所,英国) Centre for Higher Education Transformations, School of Education, University of Bristol, UK(布里斯托大学教育学院高等教育转型中心,英国) University of Oxford, UK(牛津大学,英国)

AI总结 比较三种LLM方法(GPT-4o、Mistral和定制算法DSIT-Taxonomies)从资助提案中提取和分类研究实体,发现Mistral在主题分类准确率(90.5%)上优于DSIT-Taxonomies(71.4%),且与GPT-4o质量相当。

Comments Accepted at the STI-ENID Conference. Will be presented in September 2026 in Antwerp (Belgium)

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2606.30096 2026-06-30 cs.CL cs.IT math.IT

Information Dynamics of Language Communication

语言交际的信息动力学

Leonardo S. Goodall, Andrea I. Luppi, Pedro A. M. Mediano

机构 * Calleva Research Centre, University of Oxford, UK(牛津大学卡勒瓦研究中心) St John’s College, University of Cambridge, UK(剑桥大学圣约翰学院) Montréal Neurological Institute, McGill University, Canada(蒙特利尔神经科学研究所,麦吉尔大学,加拿大) Centre for Eudaimonia and Human Flourishing, University of Oxford, UK(幸福与人类繁荣中心,牛津大学,英国) Department of Computing, Imperial College London, UK(伦敦帝国理工学院计算机系)

AI总结 提出信息论框架量化语义信息在对话中的定向流动,通过语义转移熵和语义部分信息分解测量信息传递,在四个实验中验证其能检测认知僵化对话、说服者主导作用、心理治疗质量及议论文协同贡献。

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2606.28692 2026-06-30 cs.AI

An AI agent for treatment reasoning over a biomedical tool universe

一个在生物医学工具宇宙中进行治疗推理的AI智能体

Shanghua Gao, Ayush Noori, Richard Zhu, Curtis Ginder, Zhenglun Kong, Xiaorui Su, Justin Kauffman, Benjamin S. Glicksberg, Joshua Lampert, Ankit Sakhuja, Ashwin Sawant, ATHENA-R1 Evaluation Consortium, David A. Clifton, Noa Dagan, Ran Balicer, Marinka Zitnik

机构 * Department of Biomedical Informatics, Harvard Medical School(哈佛医学院生物医学信息学系) Department of Engineering Science, University of Oxford(牛津大学工程科学系) The Ivan and Francesca Berkowitz Family Living Laboratory Collaboration at Harvard Medical School and Clalit Research Institute(哈佛医学院伊万和弗朗西斯卡·伯科维茨家族生活实验室合作与克莱利研究所) Cardiovascular Division, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School(哈佛医学院心脏病学部,布里格姆和妇女医院) The Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai(西奈山伊坎医学院人工智能与人类健康系) The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai and Mount Sinai Health System(西奈山伊坎医学院和西奈山医疗系统数字健康研究所) Mindich Child Health and Development Institute and the Departments of Pediatrics and Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai(西奈山伊坎医学院Mindich儿童健康与发展研究所及儿科学和遗传学与基因组科学系) Mount Sinai Fuster Heart Hospital, Icahn School of Medicine at Mount Sinai(西奈山伊坎医学院Fuster心脏医院) Mount Sinai AI Assurance Lab, Mount Sinai Health System(西奈山医疗系统AI保证实验室) Institute for Critical Care Medicine, Icahn School of Medicine at Mount Sinai(西奈山伊坎医学院重症监护医学研究所) Department of Medicine, Icahn School of Medicine at Mount Sinai(西奈山伊坎医学院医学系) ATHENA-R1 Evaluation Group(ATHENA-R1评估组)

AI总结 提出ATHENA-R1智能体,通过强化学习在212种生物医学工具上训练,实现迭代证据收集的治疗推理,在多个基准上超越现有模型,准确率达94.7%。

Comments Project page: https://athena.openscientist.ai Code: https://github.com/mims-harvard/ATHENA

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2606.28425 2026-06-30 cs.CR cs.AI

Tool Use Enables Undetectable Steganography in Multi-Agent LLM Systems

工具使用使多智能体LLM系统中的隐写术无法检测

Jimmy Laurence Rippin, Simon C. Marshall, David Demitri Africa, Christian Schroeder de Witt

机构 * Oxford University(牛津大学) Artificial Intelligence Security Institute (AISI)(人工智能安全研究所)

AI总结 本文研究多智能体AI系统中通过工具使用(如代码执行、网络搜索)实现无法检测的隐写通信,发现智能体可自适应构建隐写系统,并提出协调度量评估无事先约定的隐写协调风险。

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2601.22993 2026-06-30 cs.LG stat.ML

Constrained Policy Optimization with Cantelli-Bounded Value-at-Risk

具有Cantelli有界价值-at-风险的约束策略优化

Rohan Tangri, Jan-Peter Calliess

机构 * Machine Learning Research Group, University of Oxford, Oxford, United Kingdom(牛津大学机器学习研究组)

AI总结 本文提出VaR-CPO算法,通过Cantelli不等式近似非可导的VaR约束,实现安全探索和约束违反的控制,提升约束强化学习的样本效率和保守性。

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2604.22503 2026-06-30 cs.CL

Measuring and Mitigating Persona Distortions from AI Writing Assistance

衡量和缓解AI写作辅助工具中的人格扭曲

Paul Röttger, Kobi Hackenburg, Hannah Rose Kirk, Christopher Summerfield

机构 * University of Oxford(牛津大学) UK AI Security Institute(英国人工智能安全研究所)

AI总结 研究评估了AI写作辅助工具如何扭曲写作者的人格特征,通过实验发现AI使写作者显得更具观点性、能力更强和积极,但写作者对这些扭曲表示反对却仍偏好使用AI辅助文本,通过训练奖励模型缓解了部分扭曲,但影响了用户接受度。

Comments For supplementary information, code, and data see https://github.com/paul-rottger/ai-distortion

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2603.17863 2026-06-30 cs.LG cs.AI

DiscoGen: Procedural Generation of Algorithm Discovery Tasks in Machine Learning

DiscoGen:机器学习算法发现任务的程序生成

Alexander D. Goldie, Zilin Wang, Adrian Hayler, Deepak Nathani, Edan Toledo, Ken Thampiratwong, Aleksandra Kalisz, Michael Beukman, Hannah Erlebach, Alistair Letcher, Shashank Reddy, Clarisse Wibault, Theo Wolf, Charles O'Neill, Uljad Berdica, Nicholas Roberts, Saeed Rahmani, Roberta Raileanu, Shimon Whiteson, Jakob N. Foerster

机构 * University of Oxford(牛津大学) University of California, Santa Barbara(加州大学圣塔芭芭拉分校) University College London(伦敦大学学院) University of Wisconsin--Madison(威斯康星大学麦迪逊分校) Delft University of Technology(代尔夫特理工大学)

AI总结 DiscoGen通过程序生成技术创建大量机器学习算法发现任务,用于优化算法发现代理,提供固定子集用于评估,并推动新的研究方向。

Comments Accepted to ICML 2026

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2403.15212 2026-06-30 cs.CV

GCN-DevLSTM: Path Development for Skeleton-Based Action Recognition

GCN-DevLSTM:基于骨架的动作识别中的路径开发

Lei Jiang, Weixin Yang, Xin Zhang, Hao Ni

机构 * University College London(伦敦大学学院) University of Oxford(牛津大学) South China University of Technology(华南理工大学)

AI总结 本文提出GCN-DevLSTM网络,通过引入G-Dev层提升时间建模能力,有效提取骨架动作序列中的局部时间动态信息,在NTU-60、NTU-120和Chalearn2013数据集上取得竞争优势。

Journal ref Transactions on Machine Learning Research, 2026

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