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NeurIPS

Conference on Neural Information Processing Systems · 会议 · Machine Learning

2025-12-05 至 2025-12-05 共收录 14
2512.05078 2025-12-05 astro-ph.IM astro-ph.GA

Improving Posterior Inference of Galaxy Properties with Image-Based Conditional Flow Matching

通过基于图像的条件流匹配改进星系属性的后验推断

Mikaeel Yunus, John F. Wu, Benne W. Holwerda

AI总结 本文提出条件流匹配框架,结合图像与光度学数据提升星系属性推断精度,缓解尘埃-年龄退化问题。

Comments Accepted at NeurIPS 2025 ML4PS workshop

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2506.01926 2025-12-05 cs.AI cs.CL cs.LG

Large language models can learn and generalize steganographic chain-of-thought under process supervision

大语言模型可以在过程监督下学习和泛化隐写链式思维

Joey Skaf, Luis Ibanez-Lissen, Robert McCarthy, Connor Watts, Vasil Georgiv, Hannes Whittingham, Lorena Gonzalez-Manzano, David Lindner, Cameron Tice, Edward James Young, Puria Radmard

机构 * Mentorship for Alignment Research Students (MARS)(对齐研究 mentorship 项目) University College London(伦敦大学学院) Queen Mary University of London(伦敦女王学院) ML Alignment & Theory Scholars (MATS)(对齐与理论学者) Meridian Impact, Cambridge(剑桥 Meridian Impact) Universidad Carlos III de Madrid(马德里卡洛斯三世大学) Geodesic Research and University of Cambridge(Geodesic Research 和剑桥大学)

AI总结 大语言模型在过程监督下能够学习并泛化隐写链式思维,通过替换特定字符串实现推理编码,提升监控可靠性。

Comments 10 pages main text, 3 figures main text, 17 pages supplementary material, 1 figure supplementary material, accepted at NeurIPS 2025

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2503.09321 2025-12-05 cs.CV cs.AI cs.LG

DAVE: Diagnostic benchmark for Audio Visual Evaluation

DAVE: 音频视觉评估诊断基准

Gorjan Radevski, Teodora Popordanoska, Matthew B. Blaschko, Tinne Tuytelaars

机构 * KU Leuven(卢森堡大学)

AI总结 DAVE提出一个诊断基准,通过确保两种模态必要性及分解评估子类,解决多模态模型评估中的视觉偏见问题,提供更精准的模型诊断与改进指导。

Comments First two authors contributed equally

Journal ref NeurIPS 2025 Datasets & Benchmarks

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2512.04550 2025-12-05 cs.CL cs.AI

AdmTree: Compressing Lengthy Context with Adaptive Semantic Trees

AdmTree: 通过自适应语义树压缩长上下文

Yangning Li, Shaoshen Chen, Yinghui Li, Yankai Chen, Hai-Tao Zheng, Hui Wang, Wenhao Jiang, Philip S. Yu

机构 * Shenzhen International Graduate School, Tsinghua University(清华大学深圳国际研究生院) Peng Cheng Laboratory(鹏城实验室) University of Illinois Chicago(伊利诺伊大学芝加哥分校) Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ)(广东人工智能与数字经济实验室(深圳))

AI总结 AdmTree通过自适应语义树实现高效上下文压缩,保留高语义保真度并减少计算开销。

Comments NeurIPS 2025

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2512.04307 2025-12-05 cs.LG cs.AI

Evaluating Long-Context Reasoning in LLM-Based WebAgents

评估基于大语言模型的WebAgent的长上下文推理能力

Andy Chung, Yichi Zhang, Kaixiang Lin, Aditya Rawal, Qiaozi Gao, Joyce Chai

机构 * University of Michigan(密歇根大学) Amazon(亚马逊)

AI总结 本文评估了基于大语言模型的WebAgent在长上下文场景中的推理能力,发现随着上下文长度增加,性能显著下降,提出隐式RAG方法以改进任务执行。

Comments Accepted NeurIPS 25 LAW Workshop

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2512.04241 2025-12-05 math.CO q-bio.NC

Covering Relations in the Poset of Combinatorial Neural Codes

组合神经码的覆盖关系

R. Amzi Jeffs, Trong-Thuc Trang

AI总结 本文研究了组合神经码的覆盖关系,探讨了凸神经码的实现问题,并提出了关于凸神经码与多面体凸神经码等价性的猜想。

Comments To appear in Proceedings of the 4th NeurIPS Workshop on Symmetry and Geometry in Neural Representations, Proceedings of Machine Learning Research

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2512.04125 2025-12-05 cs.LG

ASCIIBench: Evaluating Language-Model-Based Understanding of Visually-Oriented Text

ASCIIBench: 评估基于语言模型的视觉文本理解

Kerry Luo, Michael Fu, Joshua Peguero, Husnain Malik, Anvay Patil, Joyce Lin, Megan Van Overborg, Ryan Sarmiento, Kevin Zhu

机构 * Algoverse AI Research(Algoverse AI研究院)

AI总结 ASCIIBench通过评估LLM生成ASCII艺术的性能,揭示了多模态表示的局限性,并推动了针对符号视觉模态的新方法发展。

Comments Accepted to The Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS 2025): LLM Evaluation Workshop & Multimodal Algorithmic Reasoning Workshop

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2512.04107 2025-12-05 cs.CY cs.AI cs.HC cs.LG

Rethinking AI Evaluation in Education: The TEACH-AI Framework and Benchmark for Generative AI Assistants

重新思考教育中的AI评估:TEACH-AI框架与生成AI助手的基准测试

Shi Ding, Brian Magerko

机构 * Expressive Machinery Lab(表达性机械实验室) Georgia Institute of Technology(佐治亚理工学院)

AI总结 本文提出TEACH-AI框架,旨在通过多视角重新定义教育中AI的有效性评估,促进包容性和长期影响。

Comments 6 pages, NeurIPS 2025 Responsible Foundation Models Workshop

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2511.22037 2025-12-05 cs.CY

What AI Speaks for Your Community: Polling AI Agents for Public Opinion on Data Center Projects

人工智能为你的社区发声:通过AI代理收集数据中心项目公众意见

Zhifeng Wu, Yuelin Han, Shaolei Ren

AI总结 本文提出AI代理调查框架,利用大型语言模型评估社区对数据中心项目的意见,以指导负责任的AI发展。

Comments 35 Pages. Accepted to NeurIPS 2025 Workshop on Socially Responsible and Trustworthy Foundation Models (ResponsibleFM)

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2510.07594 2025-12-05 hep-ex cs.LG

Locality-Sensitive Hashing-Based Efficient Point Transformer for Charged Particle Reconstruction

基于局部敏感哈希的高效点变换器用于带电粒子重建

Shitij Govil, Jack P. Rodgers, Yuan-Tang Chou, Siqi Miao, Amit Saha, Advaith Anand, Kilian Lieret, Gage DeZoort, Mia Liu, Javier Duarte, Pan Li, Shih-Chieh Hsu

机构 * Georgia Institute of Technology(佐治亚理工学院) Purdue University(普渡大学) University of Washington(华盛顿大学) Princeton University(普林斯顿大学) University of California San Diego(加州大学圣地亚哥分校)

AI总结 HEPTv2通过轻量级解码器消除聚类步骤,实现高效端到端推理,提升带电粒子轨迹重建的性能和效率。

Comments Accepted to NeurIPS 2025 Machine Learning and the Physical Sciences Workshop

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2510.03163 2025-12-05 cs.CV cs.GR

ROGR: Relightable 3D Objects using Generative Relighting

ROGR:基于生成光照的可重照明3D物体

Jiapeng Tang, Matthew Levine, Dor Verbin, Stephan J. Garbin, Matthias Nießner, Ricardo Martin Brualla, Pratul P. Srinivasan, Philipp Henzler

机构 * Google Research(谷歌研究) Google Deepmind(谷歌DeepMind) Technical University of Munich(慕尼黑技术大学)

AI总结 ROGR通过生成光照模型实现可重照明的3D物体重建,采用双分支架构的光照条件NeRF,高效生成任意环境光照下的物体外观。

Comments NeurIPS 2025 Spotlight. Project page: https://tangjiapeng.github.io/ROGR

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2509.01721 2025-12-05 cs.LG

Convolutional Monge Mapping between EEG Datasets to Support Independent Component Labeling

卷积蒙日映射在EEG数据集之间进行转换以支持独立成分标注

Austin Meek, Carlos H. Mendoza-Cardenas, Austin J. Brockmeier

机构 * Department of Computer and Information Sciences University of Delaware(计算机与信息科学系德克萨斯大学) Twitch Interactive Inc.(Twitch互动公司) Department of Electrical and Computer Engineering Department of Computer and Information Sciences University of Delaware(电气与计算机工程系计算机与信息科学系德克萨斯大学)

AI总结 本文提出了一种改进的卷积蒙日映射方法,通过两种新方法实现EEG数据集之间的映射,以提高独立成分分类的准确性。

Comments Code available at: https://github.com/cniel-ud/ICWaves; Accepted to NeurIPS 2025 Workshop on Learning from Time Series for Health

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2505.16732 2025-12-05 cs.LG cs.AI stat.ML

Sequential Monte Carlo for Policy Optimization in Continuous POMDPs

连续部分可观测马尔可夫决策过程中的策略优化的序列蒙特卡洛方法

Hany Abdulsamad, Sahel Iqbal, Simo Särkkä

AI总结 本文提出了一种基于序列蒙特卡洛的策略优化方法,用于解决连续部分可观测马尔可夫决策过程中的探索与利用平衡问题。

Comments Accepted at NeurIPS 2025

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2410.15555 2025-12-05 cs.LG cs.AI stat.ML

Bayesian Concept Bottleneck Models with LLM Priors

具有LLM先验的贝叶斯概念瓶颈模型

Jean Feng, Avni Kothari, Luke Zier, Chandan Singh, Yan Shuo Tan

机构 * University of California, San Francisco(加州大学旧金山分校) Microsoft Research(微软研究院) National University of Singapore(新加坡国立大学)

AI总结 本文提出BC-LLM模型,利用贝叶斯框架和LLM作为先验,实现高效的概念提取和可解释性提升。

Comments 2025 Conference on Neural Information Processing Systems

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