LLM Agent Training

LLM: Large Language Model

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54 papers in the last four weeks, up 145% on the four weeks before. 0.5% of all new papers.

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From History to State: Constant-Context Skill Learning for LLM Agents
May 6, 2026Haoyang Xie, Xinyuan Wang, Yancheng Wang +2LLM Agent Skill Learning LLM Agent Training
School of Computing and Augmented Intelligence, Arizona State University
OpenSeeker-v2: Pushing the Limits of Search Agents with Informative and High-Difficulty Trajectories
May 5, 2026Yuwen Du, Rui Ye, Shuo Tang +4Supervised Fine-Tuning Tool-Augmented Language Model Agents
1Shanghai Jiao Tong University
Terminus-4B: Can a Smaller Model Replace Frontier LLMs at Agentic Execution Tasks?
May 4, 2026Spandan Garg, Vikram Nitin, Yufan HuangAI Coding Agents Small Language Models
Microsoft USA
The Conversations Beneath the Code: Triadic Data for Long-Horizon Software Engineering Agents
May 4, 2026Yelin KimSoftware Engineering Agents Human-AI Interaction
Independent Researcher
SciResearcher: Scaling Deep Research Agents for Frontier Scientific Reasoning
May 2, 2026Tianshi Zheng, Rui Wang, Xiyun Li +5AI for Science Deep Research Agents
HKUST · CUHK · Tencent AI Lab
MAD-OPD: Breaking the Ceiling in On-Policy Distillation via Multi-Agent Debate
May 2, 2026Jianze Wang, Ying Liu, Jinlong Chen +7Multi-Agent Debate Multi-Teacher Knowledge Distillation
School of Artificial Intelligence and Automation, Huazhong University of Science and Technology · Alibaba Group
Agentic AI Systems Should Be Designed as Marginal Token Allocators
May 2, 2026Siqi ZhuLLM Agent Orchestration LLM Agent Evaluation
University of Illinois Urbana-Champaign
AutoSurfer -- Teaching Web Agents through Comprehensive Surfing, Learning, and Modeling
Apr 29, 2026Fazle Elahi Faisal, Qianhui Wu, Baolin Peng +1LLM Agent Training Web Agents
Microsoft Research
ClawGym: A Scalable Framework for Building Effective Claw Agents
Apr 29, 2026Fei Bai, Huatong Song, Shuang Sun +11Synthetic Data Generation AI Agent Benchmarks
Gaoling School of Artificial Intelligence, Renmin University of China · IQuest Research · Beihang University
Recursive Multi-Agent Systems
Apr 28, 2026Jiaru Zou, Rui Pan, Ruizhong Qiu +8Multi-Agent LLM Systems Language Modeling
Stanford University · University of Illinois Urbana-Champaign · NVIDIA +1
Toward Scalable Terminal Task Synthesis via Skill Graphs
Apr 28, 2026Zhiyuan Fan, Tinghao Yu, Yuanjun Cai +8Terminal Agents LLM Agent Trajectory Synthesis
Hunyuan Team, Tencent
DPEPO: Diverse Parallel Exploration Policy Optimization for LLM-based Agents
Apr 27, 2026Junshuo Zhang, Chengrui Huang, Feng Guo +6Reinforcement Learning RL Exploration
University of Electronic Science and Technology of China · DiDi
Poster: ClawdGo: Endogenous Security Awareness Training for Autonomous AI Agents
Apr 27, 2026Jiaqi Li, Yang Zhao, Bin Sun +3AI Agent Security LLM Agent Training
Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China · School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China · Network Management Center, China Mobile Group Liaoning Company Limited, Liaoning, China +2
Nemobot Games: Crafting Strategic AI Gaming Agents for Interactive Learning with Large Language Models
Apr 23, 2026Chee Wei Tan, Yuchen Wang, Shangxin GuoGame-Playing Agents LLM Agents
Nanyang Technological University, Singapore, Nanyang Ave., Singapore · Nautilus Software Technologies Limited, Hong Kong.
Learning to Communicate: Toward End-to-End Optimization of Multi-Agent Language Systems
Apr 23, 2026Ye Yu, Heming Liu, Haibo Jin +3Multi-Agent System Optimization LLM Agent Training
University of Illinois Urbana-Champaign, IL, USA
AgenticQwen: Training Small Agentic Language Models with Dual Data Flywheels for Industrial-Scale Tool Use
Apr 23, 2026Yuanjie Lyu, Chengyu Wang, Haonan Zheng +4Tool-Augmented Language Model Agents Agentic RL
Alibaba Group, Hangzhou, China
Supplement Generation Training for Enhancing Agentic Task Performance
Apr 22, 2026Young Min Cho, Daniele Bonadiman, Divya Bhargavi +8LLM Agent Training Prompt Optimization
University of Pennsylvania · AWS Agentic AI Labs · Amazon
DR-Venus: Towards Frontier Edge-Scale Deep Research Agents with Only 10K Open Data
Apr 21, 2026Venus Team, Sunhao Dai, Yong Deng +10Agentic RL Deep Research Agents
Ant Group
Training and Agentic Inference Strategies for LLM-based Manim Animation Generation
Apr 20, 2026Ravidu Suien Rammuni Silva, Ahmad Lotfi, Isibor Kennedy Ihianle +2RL for Code Generation Text-to-Video Generation
Department of Computer Science, Nottingham Trent University, Nottingham, United Kingdom · Department of Physics and Mathematics, Nottingham Trent University, Nottingham, United Kingdom
ComPASS: Towards Personalized Agentic Social Support via Tool-Augmented Companionship
Apr 20, 2026Zhaopei Huang, Yanfeng Jia, Jiayi Zhao +3AI Companions AI Agent Benchmarks
Renmin University of China · Beijing, China · Beihang University
Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligence
Apr 20, 2026Guanting Dong, Junting Lu, Junjie Huang +17Lifelong Learning Agents AI Agent Benchmarks
Renmin University of China · ByteDance Seed
Training LLM Agents for Spontaneous, Reward-Free Self-Evolution via World Knowledge Exploration
Apr 20, 2026Qifan Zhang, Dongyang Ma, Tianqing Fang +5Intrinsic Motivation LLM Agent Self-Improvement
1Tencent · 2The Hong Kong University of Science and Technology (Guangzhou)
AIT Academy: Cultivating the Complete Agent with a Confucian Three-Domain Curriculum
Apr 20, 2026Jiaqi Li, Lvyang Zhang, Yang Zhao +2LLM Agent Skill Learning Curriculum Learning
Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China · School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China
LiteResearcher: A Scalable Agentic RL Training Framework for Deep Research Agent
Apr 20, 2026Wanli Li, Bince Qu, Bo Pan +5Agentic RL Deep Research Agents
Zhejiang University · Simplex AI · The Hong Kong Polytechnic University
Democratizing Tool Learning with Environments Fully Simulated by a Free 8B Language Model
Apr 20, 2026Chenming Tang, Hsiu-Yuan Huang, Weijie Liu +3LLM Agent Training RL for Tool Use
♠National Key Laboratory for Multimedia Information Processing, Peking University · ♣School of Computer Science, Peking University · ∗Work done during an internship at Tencent +2
Small Model as Master Orchestrator: Learning Unified Agent-Tool Orchestration with Parallel Subtask Decomposition
Apr 18, 2026Wenzhen Yuan, Wutao Xiong, Fanchen Yu +7Multi-Agent System Optimization Multi-Agent Orchestration
Shanghai Jiao Tong University · Sichuan University · Shanghai AI Lab +2
AgentV-RL: Scaling Reward Modeling with Agentic Verifier
Apr 17, 2026Jiazheng Zhang, Ziche Fu, Zhiheng Xi +13Reward Modeling RL for Language Model Reasoning
College of Computer Science and Artificial Intelligence, Fudan University · Huazhong University of Science and Technology · The University of Hong Kong +3
CoEvolve: Training LLM Agents via Agent-Data Mutual Evolution
Apr 17, 2026Shidong Yang, Ziyu Ma, Tongwen Huang +3LLM Agent Training RL for LLM Agents
AMAP, Alibaba Group
SAT: Sequential Agent Tuning for Coordinator Free Plug and Play Multi-LLM Training with Monotonic Improvement Guarantees
Apr 17, 2026Yi Xie, Yangyang Xu, Yi Fan +1LLM Agent Training Decentralized MARL
Department of Electrical & Computer Engineering, University of Arizona Tucson, Arizona, USA · Department of Mathematical Sciences, Rensselaer Polytechnic Institute Troy, New York, USA · Amazon Web Services New York, USA
Subliminal Transfer of Unsafe Behaviors in AI Agent Distillation
Apr 16, 2026Jacob Dang, Brian Y. Xie, Omar G. YounisSubliminal Learning Language Model Distillation
UCLA · Santa Monica College · Mila, Silverstream AI

May 6, 2026, cs.AIJ/K move · Enter open · S save

From History to State: Constant-Context Skill Learning for LLM Agents

Haoyang Xie, Xinyuan Wang, Yancheng Wang, Puda Zhao+1

School of Computing and Augmented Intelligence, Arizona State University

LLM Agent Skill Learning LLM Agent Training LLM Context Management RL for LLM Agents

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Large language model (LLM) agents are increasingly used to operate browsers, files, code and tools, making personal assistants a natural deployment target. Yet personal agents face a privacy-cost-capability tension: cloud models execute multi-step workflows well but expose sensitive intermediate context to external APIs, while local models preserve privacy but remain less reliable. Both settings also pay repeatedly for long skill prompts and growing histories. We propose constant-context skill learning, a context-to-weights framework for recurring agent workflows: reusable procedures are learned in lightweight task-family modules, while inference conditions only on the current observation and a compact state block. A deterministic tracker renders this state block from task progress and supplies aligned subgoal rewards, so each module can be trained with step-level SFT and refined through online RL. Across ALFWorld, WebShop, and SciWorld, our agents achieve strong performance across Qwen3-4B, Qwen3-8B and Llama-3.1-8B. With Qwen3-8B, SFT+RL reaches 89.6% unseen success on ALFWorld, 76.8% success on WebShop, and 66.4% unseen success on SciWorld. They match or exceed strong published agent-training results while reducing prompt tokens per turn by 2--7

\times

relative to controlled ReAct prompting baselines, showing that procedural context can be moved from prompts into weights.

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Latest papers 354