AI agents

Tool use, function calling, orchestration and the protocols that let models act rather than only answer.

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arXiv Machine Learning

Oct 15

Scaling Human-AI Coding Collaboration Requires a Governable Consensus Layer

arXiv:2604.17883v2 Announce Type: replace-cross Abstract: Vibe coding turns natural-language intent into working software, but code generation alone does not give humans and agents a shared account o...

By Tianfu Wang, Zhezheng Hao, Yin Wu, Wei Wu, Haowen Yang, Linxiao Gong, Qiang Lin, Hande Dong, Nicholas Jing Yuan, Hui Xiong

agents

arXiv Computation and Language

Oct 15

MemDuet: Learning Dual-Process Memory for Long-Context Reasoning

arXiv:2610.19928v1 Announce Type: new Abstract: Reasoning over infinitely long documents is becoming a reality with recurrent memory agents. However, increasing context length exacerbates the trade-o...

By Jiangcheng Song, Haodong Jing, Yulin Mu, Lesong Tao, Jixin Wang, Jin Cui, Tianjing Ren, Runxuan Xie, Yongqiang Ma, Nanning Zheng

llms agents reinforcement-learning fine-tuning benchmarks

arXiv Computation and Language

Oct 15

Truthful and Expected-Payment-Optimal Model Routing in Graph-Based Agentic Workflows

arXiv:2610.19316v1 Announce Type: cross Abstract: Assigning routine tasks to cheaper large language model (LLM) providers can reduce generation cost, but switching providers may require processing ac...

By Jiayuan Liu, Mingyu Guo, Jiarui Gan, Vincent Conitzer

llms agents

arXiv Computation and Language

Oct 15

Seeing, Maintaining, and Learning: The Evolution of Multimodal Agent Memory

arXiv:2610.19366v1 Announce Type: cross Abstract: Multimodal models and agents have emerged to enable AI systems to learn from and interact with the real world more like humans by integrating informa...

By Minghao Guo, Qingyue Jiao, Xiujin Liu, Jianhong Pang, Ruimeng Yang, Naihao Xu, Liwei Che, Haochen Xue, Ziqi Wang, Xinying Cai, Jiaxuan Luo, Jiaxin Deng, Xuesong Ye, Jintao Qu, Wenyao Gao, Jingwen Gu, Chenyang Zhao, Shichun Liu, Guibin Zhang, Zefang Liu, Siyin Wang, Wujiang Xu, Danrui Li, Zeru Shi, Woongyeong Yeo, Shuang Liu, Wei-Chieh Huang, Weizhi Zhang, Tianyu Yang, Kangsan Kim, Yebowen Hu, Bowen Wen, Bowen Jiang, Haohao Su, Ming Yin, Sheldon Yu, Mian Zhang, Yuyan Chen, Hanrong Zhang, Kai Mei, Zihao Zhang, Mingyu Jin, Xi Zhu, Hengyi Wang, Tianxin Wei, Linyong Nan, Zhenwen Liang, Zhendong Chu, Ziqi Huang, Yongye Su, Sixun Dong, Shujian Liu, Kaiqu Liang, Jiaojiao Han, Zhaoye Fei, Kun Wang, Shihan Dou, Zhichun Guo, Xingjian Diao, Zeqi Gu, Heng Wang, Tao Feng, Cheng Qian, Hamid Palangi, Silei Xu, Xi Yun, Yi Zhu, Shilong Liu, Qingsong Wen, Sung Ju Hwang, Zuxuan Wu, Yu-Gang Jiang, Yiyu Shi, Dimitris N. Metaxas, Jiaxuan You, Julian McAuley, Mengdi Wang, Jiawei Han, Philip S. Yu, Ziyi Ye

rag agents multimodal

arXiv AI

Oct 15

Should SLMs be in the Driver's Seat? A Study of Local Models as Interpreters in Cloud-Written Agent Programs

arXiv:2610.14209v1 Announce Type: new Abstract: The most accurate agents executing user-provided tasks are driven by large, cloud-hosted models, which solve them by reading the private data of the us...

By Boris Radovi\v{c}, Marco Canini, Veljko Pejovi\'c

agents

arXiv AI

Oct 15

RewardHarness: Self-Evolving Agentic Post-Training

arXiv:2605.08703v2 Announce Type: replace Abstract: Aligning generative models with human preferences remains a central challenge. While RLHF is widely adopted, it relies on large-scale preference da...

By Yuxuan Zhang, Cong Wei, Penghui Du, Bo Li, Junwen Miao, Huaisong Zhang, Songcheng Cai, Yubo Wang, Dongfu Jiang, Yuyu Zhang, Changqian Yu, Ping Nie, Wenhu Chen, Kelsey R. Allen

llms agents reinforcement-learning

arXiv Machine Learning

Oct 15

AgentWorld: A Data Factory for Training LLM Agents from Multi-Turn Interactions

arXiv:2606.09138v2 Announce Type: replace Abstract: Training LLMs to act as capable agents requires learning from multi-turn interactions with environments. However, multi-turn interaction trajectori...

By Daoyu Wang, Mingyue Cheng, Qingchuan Li, Shuo Yu, Jie Ouyang, Qi Liu, Enhong Chen

llms agents reinforcement-learning

arXiv AI

Oct 15

On Symmetry for Characterizing Agent Heterogeneity in Multi-Agent Systems

arXiv:2610.18538v1 Announce Type: cross Abstract: Understanding agent heterogeneity can inform the design of shared and agent-specific policy representations, however existing criteria provide no uni...

By Jianhong Wang, Jonathan Lawry

agents

arXiv AI

Oct 15

RoboSimStudio: An Interactive Toolkit for Human and Agent Rapid Real2Sim of Robot Manipulation Tasks

arXiv:2610.18835v2 Announce Type: cross Abstract: It has been difficult to accurately model the physics of the interaction between a robot and the objects it manipulates, including contact mechanics,...

By Kaiyuan Chen, Shuangyu Xie, Uksang Yoo, Xinyue Zhu, Cael Magner, Alvin Zhu, Daehwa Kim, Eric Heiden, Erwin Coumans, Miles Macklin, Spencer Huang, Ken Goldberg

agents robotics

arXiv AI

Oct 15

Does self-distillation improve reasoning?

arXiv:2610.18613v1 Announce Type: cross Abstract: Self-distillation is an emerging approach that trains a model to imitate its own predictions when conditioned on privileged information, such as corr...

By Jason Ken Adhinarta, Raina Wu, Ashutosh Sharma, Avinash Balakrishnan, Rameswar Panda, Polina Golland, Yoon Kim, Zhang-Wei Hong

agents reinforcement-learning efficiency safety

arXiv AI

Oct 15

Agentic neural architecture search for clinical prediction from electronic health records: Cross-hospital knowledge transfer and computational efficiency

arXiv:2608.21712v3 Announce Type: replace Abstract: Transformer architectures for clinical prediction from electronic health records (EHRs) often require costly manual tuning and may vary across hosp...

By Deyi Li, Qi Xu, Lingyao Li, Tiansheng Wang, Muxuan Liang, Mei Liu

llms agents fine-tuning

arXiv AI

Oct 15

When "Must" Becomes "Maybe": Erosion of Workflow Constraints in LLM Agent Handoffs

arXiv:2608.24569v2 Announce Type: replace Abstract: Large language model (LLM) agents build on one another's work through summaries, plans, and other intermediate artifacts. These records let a downs...

By Yiheng Sun, Huifei Wang, Yancheng Zhu, Zhenyu Li, Zebin Zhao, Yifan Yuan

llms agents safety

arXiv AI

Oct 15

Visible but Not Avoided: State-Dependent Re-Proposal of Rejected Candidates in Catalog-Based LLM Optimization Loops

arXiv:2610.15738v1 Announce Type: new Abstract: LLM optimization loops often show the proposer the candidates it has already tried and rejected, but leave it to the proposer to avoid them. We ask whe...

By Jianlin Chen, Wenhui Chen, Chi Man Vong

llms agents

arXiv AI

Oct 15

Understanding and Reducing Misalignment in Persuasion Optimization

arXiv:2610.16070v1 Announce Type: new Abstract: Frontier models are now trained for complex multi-agent tasks, from running a company to engaging in negotiations. These tasks necessitate training mod...

By Boyi Wei, Ruta Desai, Peter Henderson, Wenyue Hua

agents reinforcement-learning safety

arXiv AI

Oct 15

Revocation Is Not Complete at Receipt: An Executable Outcome Contract for Distributed Agent-Tool Gateways

arXiv:2610.15991v1 Announce Type: new Abstract: Distributed agent workflows cache delegated authority at tool gateways. Revocation may be reported at issuer commit, transport acknowledgment, or recei...

By Lifei Liu, Haoran Yu, Danping Zhang

llms agents

arXiv AI

Oct 15

Large language model-generated patterns for epidemiological modeling: a multi-benchmark evaluation framework

arXiv:2610.15994v1 Announce Type: new Abstract: Representing individual-level behavioral heterogeneity is challenging in epidemiological modeling, particularly when empirical behavioral data are spar...

By Sophia Mao, Keshav Gandhi, Alexander Gutfraind

llms agents benchmarks safety

arXiv Computation and Language

Oct 15

Retrieve What Helps, Only When It Helps: Agentic Reinforcement Learning for Selective Retrieval-Augmented Machine Translation

arXiv:2610.19528v1 Announce Type: new Abstract: Retrieving external knowledge can improve large language model (LLM) translation by providing supplementary information such as idiom interpretations a...

By Shijun Li, Yang Liu, Najmeh Sadoughi, Dongmei Wang, Xinjie Li, Zhu Liu, Rohith Mysore Vijaya Kumar, Yuzong Liu

llms rag agents nlp reinforcement-learning

arXiv AI

Oct 15

Heterogeneous Agentic Coevolution

arXiv:2610.16078v1 Announce Type: new Abstract: Recent advances in self-improving LLM agents have demonstrated the potential of AI systems that drive their own intelligence. However, many domain-spec...

By Wenqian Ye, Ziwei Guan, Zi Yang, Shivani Modi, Cici Cong Wu, Yunlong He, Yuxin Chen, Zhengyu Zhang, Liang Luo, Venkatesh Ranganathan, Jianhui Sun, Yantao Yao, Wenlin Chen, Buyun Zhang, Ellie Dingqiao Wen, Henry Kautz, Aidong Zhang

llms agents

arXiv AI

Oct 15

Long-Horizon-Terminal-Bench 2.0: Automating Diverse Task Construction and Measuring Sustained Agent Progress

arXiv:2610.14146v1 Announce Type: new Abstract: Long-horizon terminal benchmarks measure whether an agent can sustain progress through extended workflows with process rewards, not only whether its fi...

By Zongxia Li, Zhongzhi Li, Yucheng Shi, Ruhan Wang, Junyao Yang, Chengsong Huang, Zhichao Liu, Xiyang Wu, Anhao Li, Yue Yu, Ergan Shang, Fuxiao Liu, Tong Zheng, Ninghao Liu, Lichao Sun, Haitao Mi, Leowei Liang

llms agents benchmarks

arXiv AI

Oct 15

ACED-Bench: Evaluating How LLM Agents Acquire and Act on Causal Evidence

arXiv:2610.14381v1 Announce Type: new Abstract: Large language models are increasingly used as scientific assistants, yet we still lack reliable ways to evaluate whether they can investigate a system...

By Yiwei Chen, Amila Weerasinghe, Siddharth Biswal, Utkrisht Rajkumar, Olcay Boz, Taylor Berg-Kirkpatrick, Rose Yu

llms agents benchmarks

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