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NeurIPS

Conference on Neural Information Processing Systems · 会议 · Machine Learning

2026-07-07 至 2026-07-07 共收录 3
2509.10650 2026-07-07 q-bio.NC cs.CG cs.LG 版本更新

On a Geometry of Interbrain Networks

关于脑间网络的一种几何结构

Nicolás Hinrichs, Noah Guzmán, Melanie Weber

机构 * Max Planck Institute for Human Cognitive and Brain Sciences(人类认知与脑科学研究所) Okinawa Institute of Science and Technology(冲绳科学和技术研究所) Harvard University(哈佛大学)

AI总结 受网络科学中几何见解成功整合启发,提出利用离散几何研究社交互动中神经交互动态重构,通过熵指标识别网络连通性关键转变,增强超扫描方法揭示神经机制的能力。

Comments 4 pages, 1 figure, 2 appendixes, accepted NeurIPS 2025 Workshop on Symmetry and Geometry in Neural Representations (NeurReps) and the Proceedings of the Geometry, Topology, and Machine Learning Workshop, PMLR 325:145-152

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2511.07403 2026-07-07 cs.CV cs.AI cs.CL cs.LG 版本更新

SpatialThinker: Reinforcing Scene Graph-Grounded Spatial Reasoning via Dense Rewards

空间思考者:通过密集奖励强化场景图基础的空间推理

Hunar Batra, Haoqin Tu, Hardy Chen, Yuanze Lin, Cihang Xie, Ronald Clark

机构 * University of Oxford(牛津大学) University of California, Santa Cruz(加州大学圣克鲁兹分校)

AI总结 研究针对多模态大语言模型空间推理难题,提出SpatialThinker,通过在线强化学习统一场景图生成与视觉推理,构建心理场景图并借助密集奖励推理,贡献包括基于SGG推理、高质量训练数据集及密集奖励设计。

Comments Preprint. Accepted at NeurIPS 2025 Workshops on SPACE in Vision, Language, and Embodied AI (SpaVLE) as Oral, Embodied World Models for Decision Making (EWM), Aligning Reinforcement Learning Experimentalists and Theorists (ARLET), and Scaling Environments for Agents (SEA)

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2404.01299 2026-07-07 cs.CV cs.AI cs.CL cs.LG 版本更新

CausalChaos! Dataset for Comprehensive Causal Action Question Answering Over Longer Causal Chains Grounded in Dynamic Visual Scenes

因果混沌!用于基于动态视觉场景的更长因果链上的综合因果动作问答的数据集

Paritosh Parmar, Eric Peh, Ruirui Chen, Ting En Lam, Yuhan Chen, Elston Tan, Basura Fernando

机构 * Institute of High-Performance Computing, Agency for Science, Technology and Research, Singapore(高性能计算研究所,科技研究局,新加坡) Nanyang Technological University(南洋理工大学) National University of Singapore(新加坡国立大学) Singapore Polytechnic(新加坡理工学院)

AI总结 针对因果视频问答中现有数据集因果推理深度不足的问题,利用卡通特性构建CausalChaos!数据集,含因果链等问题并引入错误答案挖掘,为因果关系建模等发展助力。

Comments NeurIPS 2024

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