AI Agent - arXivDaily 专题

2512.21578 2026-01-08 cs.AI 85%

NEMO-4-PAYPAL: Leveraging NVIDIA's Nemo Framework for empowering PayPal's Commerce Agent

NEMO-4-PAYPAL：利用NVIDIA的Nemo框架赋能PayPal的商业代理

Sudhanshu Garg, Andrew Wang, Chaitanya Kulkarni, Ali Sahami, Farhad Farahani, Sean Yun-Shiuan Chuang, Jian Wan, Srinivasan Manoharan, Uma Kona, Nitin Sharma, Linsey Pang, Prakhar Mehrotra, Jessica Clark, Mark Moyou

机构 * PayPal AI ； NVIDIA

专题命中工具调用：agent(title,abstract)；agentic(abstract)；multi-agent(abstract)；分类 cs.AI

AI总结 NEMO-4-PAYPAL利用NVIDIA Nemo框架优化PayPal商业代理，通过微调Nemotron模型提升检索性能并降低延迟与成本。

2512.16925 2026-01-08 cs.CV cs.AI cs.IR cs.MA 83%

V-Agent: An Interactive Video Search System Using Vision-Language Models

V-Agent：一种利用视觉-语言模型的交互式视频搜索系统

SunYoung Park, Jong-Hyeon Lee, Youngjune Kim, Daegyu Sung, Younghyun Yu, Young-rok Cha, Jeongho Ju

机构 * Korea Advanced Institute of Science and Technology（韩国科学技术院）

专题命中工具调用：agent(title,abstract)；multi-agent(abstract)；分类 cs.AI

AI总结 V-Agent通过多智能体协作和视觉-语言模型提升视频搜索性能，实现多模态交互与零样本性能。

Comments CIKM 2025 MMGENSR Workshop

2509.11963 2026-01-08 cs.CL 70%

ToolRM: Outcome Reward Models for Tool-Calling Large Language Models

ToolRM: 用于工具调用大型语言模型的成果奖励模型

Mayank Agarwal, Ibrahim Abdelaziz, Kinjal Basu, Merve Unuvar, Luis A. Lastras, Yara Rizk, Pavan Kapanipathi

机构 * IBM Research（IBM研究院）

专题命中工具调用：tool use(abstract)；tool-use(abstract)；分类 cs.CL

AI总结 ToolRM通过领域特定建模提升工具调用奖励模型性能，实现25%的改进并增强鲁棒性。

2508.02110 2026-01-08 cs.AI 70%

Attractive Metadata Attack: Inducing LLM Agents to Invoke Malicious Tools

吸引性元数据攻击：诱导LLM代理调用恶意工具

Kanghua Mo, Li Hu, Yucheng Long, Zhihao Li

机构 * Cyberspace Institute of Advanced Technology, Guangzhou University（广州大学网络空间研究院）； Department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University（香港理工大学电子与电气工程系）

专题命中工具调用：agent(abstract)；tool-use(abstract)；分类 cs.AI

AI总结本研究提出AMA攻击，通过操纵工具元数据诱导LLM代理调用恶意工具，揭示了系统性安全漏洞。

Comments Accepted to NeurIPS 2025

2601.03733 2026-01-08 cs.CV cs.AI cs.CL cs.CY cs.LG 67%

RadDiff: Describing Differences in Radiology Image Sets with Natural Language

RadDiff：用自然语言描述放射学图像集的差异

Xiaoxian Shen, Yuhui Zhang, Sahithi Ankireddy, Xiaohan Wang, Maya Varma, Henry Guo, Curtis Langlotz, Serena Yeung-Levy

机构 * Stanford University（斯坦福大学）

专题命中工具调用：agentic(abstract)；分类 cs.AI、cs.CL、cs.LG

AI总结 RadDiff通过多模态代理系统实现放射学图像集差异的自然语言描述，结合医学知识和多模态推理，在放射学研究配对中取得高准确率，推动临床影像分析的发展。

2601.03476 2026-01-08 eess.SY cs.AI cs.LG cs.MA cs.SY 62%

Online Decision-Making Under Uncertainty for Vehicle-to-Building Systems

在不确定环境下为车辆到建筑系统进行在线决策

Rishav Sen, Yunuo Zhang, Fangqi Liu, Jose Paolo Talusan, Ava Pettet, Yoshinori Suzue, Ayan Mukhopadhyay, Abhishek Dubey

机构 * Vanderbilt University（范德比大学）； Nissan Advanced Technology Center - Silicon Valley（日产先进技术中心-硅谷）

专题命中工具调用：planning(abstract)；分类 cs.AI、cs.LG

AI总结本研究提出了一种基于马尔可夫决策过程的在线决策方法，用于解决车辆到建筑系统在不确定环境下的优化问题，通过在线搜索和启发式剪枝提升效率，实验表明其优于现有方法。

Comments 17 pages, 2 figures, 10 tables. Published in the Proceedings of the 16th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS '25), May 06--09, 2025, Irvine, CA, USA

Journal ref Proceedings of 16th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS), 2025

2506.08726 2026-01-08 cs.CL cs.AI 62%

Improved LLM Agents for Financial Document Question Answering

改进的金融文档问答大型语言模型代理

Nelvin Tan, Zian Seng, Liang Zhang, Yu-Ching Shih, Dong Yang, Amol Salunkhe

机构 * American Express（美国美国运通）

专题命中工具调用：agent(abstract)；分类 cs.AI、cs.CL

AI总结本文提出改进的金融文档问答代理，通过实验展示其在无 oracle 标签情况下的有效性，并引入更安全的计算代理。

Comments 13 pages, 6 figures. More analysis is added to Appendix C

2601.03782 2026-01-08 cs.RO cs.AI cs.CV 57%

PointWorld: Scaling 3D World Models for In-The-Wild Robotic Manipulation

PointWorld: 为真实世界机器人操作扩展3D世界模型

Wenlong Huang, Yu-Wei Chao, Arsalan Mousavian, Ming-Yu Liu, Dieter Fox, Kaichun Mo, Li Fei-Fei

机构 * Stanford University（斯坦福大学）； NVIDIA（英伟达）

专题命中工具调用：tool use(abstract)；分类 cs.AI

AI总结 PointWorld通过统一状态和动作的3D点流模型，实现了在真实世界中机器人操作的高效预测与控制，无需额外演示或训练。

2505.11964 2026-01-08 cond-mat.supr-con cond-mat.mtrl-sci 50%

Accelerating the Search for Superconductors Using Machine Learning

利用机器学习加速超导体的搜索

Suhas Adiga, Umesh V. Waghmare

专题命中工具调用：workflow(abstract)

AI总结本文利用机器学习方法，基于量子结构图的描述符，开发出预测超导体临界温度Tc的随机森林模型，通过清理数据库和分析化学组成，实现了对超导材料的高效筛选和预测。

Journal ref Comput. Mater. Sci., 263, 114453 (2026)

2411.16021 2026-01-08 astro-ph.HE 50%

Measurement of Very-high-energy Diffuse Gamma-ray Emissions from the Galactic Plane with LHAASO-WCDA

利用LHAASO-WCDA测量银河系平面非常高的能量弥散伽马射线辐射

The LHAASO Collaboration, Zhen Cao, F. Aharonian, Y. X. Bai, Y. W. Bao, D. Bastieri, X. J. Bi, Y. J. Bi, W. Bian, A. V. Bukevich, C. M. Cai, W. Y. Cao, Zhe Cao, J. Chang, J. F. Chang, A. M. Chen, E. S. Chen, H. X. Chen, Liang Chen, Long Chen, M. J. Chen, M. L. Chen, Q. H. Chen, S. Chen, S. H. Chen, S. Z. Chen, T. L. Chen, X. B. Chen, X. J. Chen, Y. Chen, N. Cheng, Y. D. Cheng, M. C. Chu, M. Y. Cui, S. W. Cui, X. H. Cui, Y. D. Cui, B. Z. Dai, H. L. Dai, Z. G. Dai, Danzengluobu, Y. X. Diao, X. Q. Dong, K. K. Duan, J. H. Fan, Y. Z. Fan, J. Fang, J. H. Fang, K. Fang, C. F. Feng, H. Feng, L. Feng, S. H. Feng, X. T. Feng, Y. Feng, Y. L. Feng, S. Gabici, B. Gao, C. D. Gao, Q. Gao, W. Gao, W. K. Gao, M. M. Ge, T. T. Ge, L. S. Geng, G. Giacinti, G. H. Gong, Q. B. Gou, M. H. Gu, F. L. Guo, J. Guo, X. L. Guo, Y. Q. Guo, Y. Y. Guo, Y. A. Han, O. A. Hannuksela, M. Hasan, H. H. He, H. N. He, J. Y. He, X. Y. He, Y. He, S. Hernández-Cadena, Y. K. Hor, B. W. Hou, C. Hou, X. Hou, H. B. Hu, S. C. Hu, C. Huang, D. H. Huang, J. J. Huang, T. Q. Huang, W. J. Huang, X. T. Huang, X. Y. Huang, Y. Huang, Y. Y. Huang, X. L. Ji, H. Y. Jia, K. Jia, H. B. Jiang, K. Jiang, X. W. Jiang, Z. J. Jiang, M. Jin, S. Kaci, M. M. Kang, I. Karpikov, D. Khangulyan, D. Kuleshov, K. Kurinov, B. B. Li, Cheng Li, Cong Li, D. Li, F. Li, H. B. Li, H. C. Li, Jian Li, Jie Li, K. Li, L. Li, R. L. Li, S. D. Li, T. Y. Li, W. L. Li, X. R. Li, Xin Li, Y. Z. Li, Zhe Li, Zhuo Li, E. W. Liang, Y. F. Liang, S. J. Lin, B. Liu, C. Liu, D. Liu, D. B. Liu, H. Liu, H. D. Liu, J. Liu, J. L. Liu, J. R. Liu, M. Y. Liu, R. Y. Liu, S. M. Liu, W. Liu, X. Liu, Y. Liu, Y. Liu, Y. N. Liu, Y. Q. Lou, Q. Luo, Y. Luo, H. K. Lv, B. Q. Ma, L. L. Ma, X. H. Ma, J. R. Mao, Z. Min, W. Mitthumsiri, G. B. Mou, H. J. Mu, Y. C. Nan, A. Neronov, K. C. Y. Ng, M. Y. Ni, L. Nie, L. J. Ou, P. Pattarakijwanich, Z. Y. Pei, J. C. Qi, M. Y. Qi, J. J. Qin, A. Raza, C. Y. Ren, D. Ruffolo, A. Sáiz, M. Saeed, D. Semikoz, L. Shao, O. Shchegolev, Y. Z. Shen, X. D. Sheng, Z. D. Shi, F. W. Shu, H. C. Song, Yu. V. Stenkin, V. Stepanov, Y. Su, D. X. Sun, H. Sun, Q. N. Sun, X. N. Sun, Z. B. Sun, N. H. Tabasam, J. Takata, P. H. T. Tam, H. B. Tan, Q. W. Tang, R. Tang, Z. B. Tang, W. W. Tian, C. N. Tong, L. H. Wan, C. Wang, G. W. Wang, H. G. Wang, H. H. Wang, J. C. Wang, K. Wang, Kai Wang, Kai Wang, L. P. Wang, L. Y. Wang, L. Y. Wang, R. Wang, W. Wang, X. G. Wang, X. J. Wang, X. Y. Wang, Y. Wang, Y. D. Wang, Z. H. Wang, Z. X. Wang, Zheng Wang, D. M. Wei, J. J. Wei, Y. J. Wei, T. Wen, S. S. Weng, C. Y. Wu, H. R. Wu, Q. W. Wu, S. Wu, X. F. Wu, Y. S. Wu, S. Q. Xi, J. Xia, J. J. Xia, G. M. Xiang, D. X. Xiao, G. Xiao, Y. L. Xin, Y. Xing, D. R. Xiong, Z. Xiong, D. L. Xu, R. F. Xu, R. X. Xu, W. L. Xu, L. Xue, D. H. Yan, J. Z. Yan, T. Yan, C. W. Yang, C. Y. Yang, F. F. Yang, L. L. Yang, M. J. Yang, R. Z. Yang, W. X. Yang, Y. H. Yao, Z. G. Yao, X. A. Ye, L. Q. Yin, N. Yin, X. H. You, Z. Y. You, Y. H. Yu, Q. Yuan, H. Yue, H. D. Zeng, T. X. Zeng, W. Zeng, M. Zha, B. B. Zhang, B. T. Zhang, F. Zhang, H. Zhang, H. M. Zhang, H. Y. Zhang, J. L. Zhang, Li Zhang, P. F. Zhang, P. P. Zhang, R. Zhang, S. R. Zhang, S. S. Zhang, W. Y. Zhang, X. Zhang, X. P. Zhang, Yi Zhang, Yong Zhang, Z. P. Zhang, J. Zhao, L. Zhao, L. Z. Zhao, S. P. Zhao, X. H. Zhao, Z. H. Zhao, F. Zheng, W. J. Zhong, B. Zhou, H. Zhou, J. N. Zhou, M. Zhou, P. Zhou, R. Zhou, X. X. Zhou, X. X. Zhou, B. Y. Zhu, C. G. Zhu, F. R. Zhu, H. Zhu, K. J. Zhu, Y. C. Zou, X. Zuo

专题命中工具调用：tool use(abstract)

AI总结 LHAASO-WCDA测量银河系平面高能弥散伽马射线辐射，发现能谱软化并揭示其空间分布与气体柱密度的偏离。

Journal ref Physical Review Letters 134, 081002 (2025)

1. 工具调用 10 篇