arXivDaily arXiv每日学术速递 周一至周五更新

高校专区

Shanghai Jiao Tong University(上海交通大学)

2026-07-09 至 2026-07-09 共收录 10
2607.07708 2026-07-09 cs.CL cs.AI cs.CE cs.LG 新提交

Accurate, Interdisciplinary and Transparent Structure-property Understanding with Deep Native Structural Reasoning

通过深度原生结构推理实现准确、跨学科和透明的结构-属性理解

Chen Tang, Yizhou Wang, Jianyu Wu, Lintao Wang, Shixiang Tang, Pengze Li, Encheng Su, Jun Yao, Jiabei Xiao, Yuqi Shi, Jielan Li, Hongxia Hao, Zhangyang Gao, Fang Wu, Ben Fei, Xiangyu Yue, Pan Tan, Bozitao Zhong, Jinouwen Zhang, Aoran Wang, Yan Lu, Jiaheng Liu, Xinzhu Ma, Liang Hong, Mingyue Zheng, Phil Torr, Bowen Zhou, Wanli Ouyang, Lei Bai

机构 * Shanghai Artificial Intelligence Laboratory(上海人工智能实验室) The Chinese University of Hong Kong(香港中文大学) Shanghai Jiao Tong University(上海交通大学) Fudan University(复旦大学) University of Sydney(悉尼大学) Nanjing University(南京大学) University of Oxford(牛津大学) The University of Science and Technology of China(中国科学技术大学) Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences(药物发现与设计中心、国家药物研究重点实验室、上海中医药材料医学研究所、中国科学院) University of Chinese Academy of Sciences(中国科学院大学) Stanford University(斯坦福大学)

AI总结 研究聚焦利用人工智能解释结构-属性关系的挑战,提出多模态科学基础模型SciReasoner,通过离散化结构信息为可寻址单元进行推理,在多领域基准测试中表现出色,实现准确预测与可解释科学推理的结合。

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2607.07320 2026-07-09 cs.CV 新提交

SoccerNet 2026 Challenges Results

SoccerNet 2026挑战结果

Anthony Cioppa, Silvio Giancola, Håkan Ardö, Mohamad Dalal, Jan Held, Jérémie Ochin, Jiayuan Rao, Karen Sanchez, Renaud Vandeghen, Artur Xarles, Olivier Barnich, Albert Clapés, Mathieu Delvaux, Sergio Escalera, Bernard Ghanem, Cédric Hons, Antoine Houet, Sotiris Manitsaris, Tom Michel, Pierre Miralles, Thomas B. Moeslund, Mikael Nilsson, Bogdan Stanciulescu, Marc Van Droogenbroeck, Yanfeng Wang, Weidi Xie, Faisal Altawijri, Mohamed Atef, Semen Budennyy, Vasiliy Chelpanov, Puhua Chen, Yixin Chen, Lechao Cheng, Jianling Chu, Ju-Seong Do, Oleg Durygin, Omar Fetouh, Mirco Fuchs, Youssef Ghallab, Falguni Ghosh, Wonjun Heo, Yufeng Hu, Weixuan Huang, Phuong-Linh Huynh-Ha, Matvey Isupov, Yangguang Ji, Siyuan Jiang, Zhenxiang Jiang, Wonyong Jo, Ho-Young Jung, SeongHeon Kang, MinJae Kim, Youngseon Kim, Jakub Komosa, Artem Konshin, Trung-Hoang Le, Jongmin Lee, Lingling Li, Litao Li, Vadim Linkov, Fang Liu, Haoxuan Ma, Shun Makino, Ismail Mathkour, Konstantin Mitin, Mikhail Moiseev, Takumi Nagaya, Yuki Nakamura, Thanh-Khoi Nguyen, Hoang-Phuc Nguyen, Trong-Thuan Nguyen, Christian Orduz, Kwanyong Park, Fabian Perez, Parthsarthi Rawat, SuHyun Rim, Hoover Rueda-Chacón, Atom Scott, Minori Sugimura, Yuyang Sun, Shengeng Tang, Minh-Triet Tran, Ikuma Uchida, Juan Vanegas, Thanh-Nhan Vo, Jiangtao Wang, Yaxiong Wang, Xiaogang Wang, Ruifeng Wang, Rio Watanabe, Jiali Wen, Yongliang Wu, Di Yang, Xu Yang, Zhuo Yang, Xinyu Ye, Yibo Yu, Zihan Zhai, Yu Zhang, Zhenyu Zhao, Zhun Zhong, Yixi Zhou, Xingyu Zhu, Wenbo Zhu, Julian Ziegler

机构 * University of Liège(列日大学) King Abdullah University of Science and Technology(阿卜杜拉国王科技大学) Spiideo(斯皮迪奥公司) Aalborg University(奥尔堡大学) SpAItial(斯帕蒂亚尔公司) Center for Robotics, Mines Paris, PSL(巴黎矿业学院机器人中心(巴黎文理研究大学)) Footovision(Footovision公司) Shanghai Jiao Tong University(上海交通大学) Universitat de Barcelona(巴塞罗那大学) Computer Vision Center(计算机视觉中心) EVS Broadcast Equipment(EVS广播设备公司) Pioneer Center for Artificial Intelligence(先锋人工智能中心) Lund University(隆德大学) TAHAKOM(TAHAKOM公司) Mohamed Bin Zayed University for Artificial Intelligence (MBZUAI)(穆罕默德·本·扎耶德人工智能大学) Sber AI(Sber人工智能公司) Salute For Business(Salute For Business公司) Intelligent Perception and Image Understanding Lab, Xidian University(西安电子科技大学智能感知与图像理解实验室) South China University of Technology(华南理工大学) Hefei University of Technology(合肥工业大学) Kyungpook National University(庆北国立大学) Leipzig University of Applied Sciences(莱比锡应用科学大学) Friedrich-Alexander University Erlangen-Nuremberg(埃尔朗根-纽伦堡大学) University of Seoul(首尔大学) Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China(电子科技大学深圳高等研究院) Nanjing University(南京大学) University of Science, Ho Chi Minh City(胡志明市科技大学) Nanyang Technological University(南洋理工大学) National University of Singapore(新加坡国立大学)

AI总结 SoccerNet 2026挑战涵盖五项体育视频理解视觉任务,为每项任务提供数据、协议和基线。众多团队参与,本文介绍任务、评估协议,展示排行榜并总结领先提交内容,记录各任务当前状态。

Comments 40 pages

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2607.07288 2026-07-09 cs.CV 新提交

InfraQR: Edge-Placed QR-Inspired Structured Patch Attacks on Infrared Vision-Language Models

InfraQR:对红外视觉语言模型的边缘放置的受QR码启发的结构化补丁攻击

Xin Li, Jiaju Han, Ma Yaqi, Chengyin Hu, Yingying Zhao, Jiahuan Long, Fengyu Zhang, Yahui Chai

机构 * China University of Petroleum-Beijing at Karamay(中国石油大学(北京)克拉玛依校区) Guizhou University(贵州大学) Shenzhen Research Institute of Big Data(深圳大数据研究院) Shanghai Jiao Tong University(上海交通大学)

AI总结 研究红外视觉语言模型对局部结构化扰动的鲁棒性,提出InfraQR攻击方法,沿图像边界放置结构化补丁并通过替代编码器优化网格单元,实验表明该方法能大幅降低分类器准确率,使对抗图像影响黑盒模型,凸显模型易受此类扰动影响。

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2607.07103 2026-07-09 cs.LG cs.DB 新提交

A knowledge-augmented dataset of high-risk driving scenarios with LLM annotations for autonomous driving

一个用于自动驾驶的具有大语言模型注释的高风险驾驶场景知识增强数据集

Heye Huang, Jingguang Li, Zhiyuan Zhou, Paul Liang, Mingyu Wu, Kitae Jang, Jianqiang Wang

机构 * Korea Advanced Institute of Science and Technology(韩国科学技术院) Fudan University(复旦大学) Massachusetts Institute of Technology(麻省理工学院) Shanghai Jiao Tong University(上海交通大学) Tsinghua University(清华大学)

AI总结 研究自动驾驶中高风险场景数据不足问题,核心方法是构建K-Risk数据集,整合多源轨迹数据并利用大语言模型生成注释,主要贡献是为自动驾驶开发和评估提供标准化基础。

Comments 22 pages, 9 figures

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2607.06699 2026-07-09 cs.RO 新提交

RoboSnap: One-Shot Real-to-Sim Scene Generation for Generalizable Robot Learning and Evaluation

RoboSnap:用于可泛化机器人学习与评估的一次性真实到模拟场景生成

Shujie Zhang, Jingkun Yi, Weipeng Zhong, Zirui Zhou, Yangkun Zhu, Hanqing Wang, Xudong Xu, Weinan Zhang, Chunhua Shen

机构 * Shanghai AI Laboratory(上海人工智能实验室) Shanghai Jiao Tong University(上海交通大学) Zhejiang University(浙江大学) Tsinghua University(清华大学)

AI总结 针对构建物理稳定且视觉逼真场景缓慢昂贵的问题,提出RoboSnap框架,通过分层设计将单张RGB图像转为模拟场景,实验证明其能实现轨迹重放等,还引入DROID-Sim数据集,凸显真实到模拟方法对机器人学习评估的价值。

Comments 24 pages, 16 figures, Project page: https://robosnap.github.io

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2607.04653 2026-07-09 cs.CV 新提交

Enhancing Video Physical Consistency via Role-aware Joint Training and Modality-decoupled Denoising

通过角色感知联合训练和模态解耦去噪增强视频物理一致性

Guangting Zheng, Haojing Chen, Hao Li, Jingtao Zhang, Zhen Yang, Xiaosong Jia, Xue Yang, Shaofeng Zhang, Yanyong Zhang

机构 * University of Science and Technology of China(中国科学技术大学) University of Electronic Science and Technology of China(电子科技大学) Fudan University(复旦大学) Georgia Institute of Technology(佐治亚理工学院) Shanghai Jiao Tong University(上海交通大学)

AI总结 研究针对视频扩散模型长程物理一致性挑战,提出VPT微调框架。通过角色感知信号清晰建模不同物理角色,采用模态解耦去噪策略及损失权重衰减,引入跨步自动引导,增强物理动力学,提升物理一致性与视觉质量。

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2607.04434 2026-07-09 cs.RO cs.AI cs.CV cs.GR 新提交

RoboDojo: A Unified Sim-and-Real Benchmark for Comprehensive Evaluation of Generalist Robot Manipulation Policies

RoboDojo:用于综合评估通用机器人操作策略的统一模拟与现实基准测试

Tianxing Chen, Yue Chen, Zixuan Li, Junyuan Tang, Kailun Su, Haoran Lu, Weijie Wan, Baijun Chen, Songling Liu, Haowen Yan, Honghao Su, Zhiyang Dou, Kaixuan Wang, Dandan Zhang, Yunze Liu, Yan Qin, Qiwei Liang, Qiwei Wu, Zijian Lin, Wenwei Lin, Yuran Wang, Minghua He, Tianshu Wu, Ruihai Wu, Jingquan Zhou, Kai-Chong Lei, Haibao Yu, Yuanfeng Ji, Weiyang Jin, Guanyu Lin, Xiaofan Li, Qi Xiong, Renjing Xu, Zhongyu Li, Wenhao Chai, Enze Xie, Ziwei Wang, Yao Mu, Hao Dong, Wojciech Matusik, Mingyu Ding, Wenbo Ding, Ping Luo, Masayoshi Tomizuka

机构 * UC Berkeley(加州大学伯克利分校) THU(清华大学) PKU(北京大学) Stanford(斯坦福大学) MIT(麻省理工学院) UNC(北卡罗来纳大学) Princeton(普林斯顿大学) CMU(卡内基梅隆大学) NUS(新加坡国立大学) NTU(南洋理工大学) CUHK(香港中文大学) SJTU(上海交通大学) HKUST (GZ)(香港科技大学(广州)) ZJU(浙江大学) Yale(耶鲁大学)

AI总结 现有基准测试在系统评估通用机器人操作策略能力方面有限,本文引入RoboDojo统一基准测试,含模拟与现实任务,支持多维度评估及可扩展评估,还建立了公共排行榜与系统分析。

Comments Website: https://robodojo-benchmark.com/, Code: https://github.com/RoboDojo-Benchmark/RoboDojo, Leaderboard: https://robodojo-benchmark.com/leaderboard

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2603.15685 2026-07-09 cs.MM cs.AI cs.CV cs.SD 版本更新

DASH: Dynamic Audio-Driven Semantic Chunking for Efficient Omnimodal Token Compression

DASH:动态音频驱动的语义分块以实现高效的多模态令牌压缩

Bingzhou Li, Tao Huang

机构 * Shanghai Jiao Tong University(上海交通大学) Tongji University(同济大学)

AI总结 DASH通过动态音频驱动的语义分块方法,有效压缩多模态令牌,提升推理效率,优于传统固定窗口分块和注意力剪枝方法。

Comments ECCV 2026

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2510.02999 2026-07-09 cs.CR cs.AI 版本更新

NonTextual Target Attack

非文本目标攻击

Xinzhe Huang, Wenjing Hu, Tianhang Zheng, Kedong Xiu, Hongsheng Hu, Xiaojun Jia, Di Wang, Zhan Qin, Kui Ren

机构 * State Key Laboratory of Blockchain and Data Security, Zhejiang University(区块链与数据安全国家重点实验室,浙江大学) Hangzhou High-Tech Zone, Binjiang Institute of Blockchain and Data Security, Hangzhou(杭州高新技术区,滨江区块链与数据安全研究院) School of Cyberspace Security, Nanjing University of Science and Technology(网络安全学院,南京理工大学) School of Computer Science, Shanghai Jiao Tong University(计算机科学学院,上海交通大学) College of Computing and Data Science, Nanyang Technological University(计算与数据科学学院,新加坡国立大学) King Abdullah University of Science and Technology (KAUST)(卡布斯科学与技术大学)

AI总结 针对现有大语言模型越狱攻击的局限,提出非文本目标攻击NTA,通过非文本约束目标最大化不安全概率,分解目标便于优化,扩展攻击空间,在AdvBench上对安全对齐的大语言模型仅100次迭代,平均成功率达96.8%,性能远超现有攻击。

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2508.12265 2026-07-09 cs.CL 版本更新

Fast, Slow, and Tool-augmented Thinking for LLMs: A Review

大语言模型的快速、慢速和工具增强思维:综述

Xinda Jia, Jinpeng Li, Zezhong Wang, Jingjing Li, Xingshan Zeng, Yasheng Wang, Weinan Zhang, Yong Yu, Weiwen Liu

机构 * School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China(上海交通大学机械工程学院) School of Computer Science, Shanghai Jiao Tong University, Shanghai 200240, China(上海交通大学计算机科学学院) Huawei Technologies Co., Ltd., Beijing 100084, China(华为技术有限公司) Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Hong Kong 999077, China(香港中文大学系统工程与工程管理系) Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong 999077, China(香港中文大学计算机科学与工程系) Huawei Hong Kong Research Center, Hong Kong 999077, China(华为香港研究中心)

AI总结 综述大语言模型推理进展,基于认知心理学提出LLM推理策略分类法,沿快速/慢速、内部/外部两个知识边界分类,系统调查相关工作并依关键因素归类方法,指出其面临的挑战与未来方向。

Comments The article has been accepted by Frontiers of Computer Science (FCS), with the DOI: {10.1007/s11704-026-51673-0}

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