Agentic RL

RL: Reinforcement Learning

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28 papers in the last four weeks, up 300% on the four weeks before. 0.3% of all new papers.

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Libra: Efficient Resource Management for Agentic RL Post-Training
Jun 2, 2026Kaiwen Chen, Xin Tan, Jingzong Li +6Agentic RL Reinforcement Learning
The Chinese University of Hong Kong · The Hang Seng University of Hong Kong · Independent Researcher
Policy and World Modeling Co-Training for Language Agents
Jun 1, 2026Ning Lu, Baijiong Lin, Shengcai Liu +9Agentic RL World Model Learning
Southern University of Science and Technology · Hong Kong University of Science and Technology · Hong Kong University of Science and Technology (Guangzhou) +2
Learning When Not to Act: Mitigating Tool Abuse in Agentic Reinforcement Learning
Jun 1, 2026Liuji Chen, Dianxing Tang, Xing Shi +4Agentic RL RL for Language Model Reasoning
1NLPR, Institute of Automation, Chinese Academy of Sciences · 3Zhejiang University · 2ByteDance
RDA: Reward Design Agent for Reinforcement Learning
Jun 1, 2026Hojoon Lee, Ajay Subramanian, Ben Abbatematteo +4Agentic RL Reinforcement Learning
Meta · Holiday Robotics · Boston Dynamics
Skill Reuse as Compression in Agentic RL
May 29, 2026Zhikun Xu, Yu Feng, Jacob Dineen +3Agentic RL Minimum Description Length
Arizona State University · University of Pennsylvania · University of Southern California
Agentic Transformers Provably Learn to Search via Reinforcement Learning
May 29, 2026Tong Yang, Yu Huang, Yingbin Liang +1Policy Gradient Agentic RL
Department of Electrical and Computer Engineering, Carnegie Mellon University · Department of Statistics and Data Science, Wharton School, University of Pennsylvania · Department of Electrical and Computer Engineering, The Ohio State University +1
GUI-C $^2$ : Coarse-to-Fine GUI Grounding via Difficulty-Aware Reinforcement Learning
May 29, 2026Junlong Li, Chao Hao, Lap-Pui Chau +1Multimodal Grounding Agentic RL
The Hong Kong Polytechnic University
Beyond Trajectory Rewards: Step-level Credit Assignment for Agentic Search via Graph Modeling
May 28, 2026Yuchen Liu, Yingjie Feng, Lixiong Qin +5Reward Modeling Agentic RL
Beijing University of Posts and Telecommunications · Li Auto Inc.
GAPD: Gold-Action Policy Distillation for Agentic Reinforcement Learning in Knowledge Base Question Answering
May 28, 2026Xin Sun, Jianan Xie, Zhongqi Chen +6Agentic RL Knowledge Graph Question Answering
University of Science and Technology of China · 2NLPR, MAIS, Institute of Automation, Chinese Academy of Sciences · 3ShanghaiTech University +1
Skill0.5: Joint Skill Internalization and Utilization for Out-of-Distribution Generalization in Agentic Reinforcement Learning
May 27, 2026Jiapeng Zhu, Jianxiang Yu, Yibo Zhao +5Agentic RL OOD Generalization
1East China Normal University, 2Meituan Longcat Team · 1East China Normal University · 2Meituan Longcat Team
Cyclical Entropy Eruption: Entropy Dynamics in Agent Reinforcement Learning
May 27, 2026Wendi Li, Shawn Im, Sharon LiAgentic RL Reinforcement Learning
Department of Computer Sciences, University of Wisconsin–Madison
Efficient Agentic Reinforcement Learning with On-Policy Intrinsic Knowledge Boundary Enhancement
May 26, 2026Dingwei Chen, Zefang Zong, Zhipeng Ma +5Agentic RL LLM Agent Training
Tencent Inc · The Chinese University of Hong Kong · Shenzhen MSU-BIT University
The MiniMax-M2 Series: Mini Activations Unleashing Max Real-World Intelligence
May 26, 2026MiniMax, :, Aili Chen +204Mixture-of-Experts Language Models Agentic RL
From Correctness to Preference: A Framework for Personalized Agentic Reinforcement Learning
May 22, 2026Ranxu zhang, zeyang li, Jiacheng Huang +5Agentic RL Reinforcement Learning
University of Science and Technology of China · Alibaba Group
Agentic-VLA: Efficient Online Adaptation for Vision-Language-Action Models
May 21, 2026Ruofan Jin, Zaixi ZhangAgentic RL VLM Adaptation
Scinetics.
ParaVT: Taming the Tool Prior Paradox for Parallel Tool Use in Agentic Video Reinforcement Learning
May 19, 2026Zuhao Yang, Kaichen Zhang, Sudong Wang +7Tool Use in VLMs Agentic RL
2NTU · 6LMMs-Lab · Work largely done during Z.Y., K.Z., S.W., and K.W.’s internship at MiroMind. +4
EnvFactory: Scaling Tool-Use Agents via Executable Environments Synthesis and Robust RL
May 18, 2026Minrui Xu, Zilin Wang, Mengyi DENG +12Tool-Augmented Language Model Agents Agentic RL
LARK, HKUST (GZ) · University of Cambridge · UCL +2
AstraFlow: Dataflow-Oriented Reinforcement Learning for Agentic LLMs
May 15, 2026Haizhong Zheng, Yizhuo Di, Jiahui Wang +7Agentic RL Reinforcement Learning
1Carnegie Mellon University · University of Michigan · 3UC Berkeley +1
Self-Distilled Agentic Reinforcement Learning
May 14, 2026Zhengxi Lu, Zhiyuan Yao, Zhuowen Han +8Agentic RL Self-Distillation
Zhejiang University · Meituan · Tsinghua University
Agentifying Patient Dynamics within LLMs through Interacting with Clinical World Model
May 14, 2026Minghao Wu, Yuting Yan, Zhenyang Cai +9Agentic RL Clinical Decision Support
The Chinese University of Hong Kong, Shenzhen · Beijing Hospital
Resolving Action Bottleneck: Agentic Reinforcement Learning Informed by Token-Level Energy
May 14, 2026Langzhou He, Junyou Zhu, Yue Zhou +7Agentic RL Token-Level Credit Assignment
University of Illinois Chicago · Potsdam Institute for Climate Impact Research · Technical University of Berlin +3
ToolCUA: Towards Optimal GUI-Tool Path Orchestration for Computer Use Agents
May 12, 2026Xuhao Hu, Xi Zhang, Haiyang Xu +6Agentic RL RL for GUI Agents
Tongyi Lab, Alibaba Group · Fudan University · Shanghai Artificial Intelligence Laboratory
Learning Agentic Policy from Action Guidance
May 12, 2026Yuxiang Ji, Zengbin Wang, Yong Wang +6Agentic RL Reinforcement Learning
1Xiamen University · 2AMAP, Alibaba Group · Work done during internship at AMAP, Alibaba Group +1
On-Policy Self-Evolution via Failure Trajectories for Agentic Safety Alignment
May 12, 2026Bo Yin, Qi Li, Xinchao WangAgentic RL LLM Safety Alignment
National University of Singapore
Dynamic Skill Lifecycle Management for Agentic Reinforcement Learning
May 11, 2026Junhao Shen, Teng Zhang, Xiaoyan Zhao +1Agentic RL LLM Agent Skill Learning
Database Group, The Chinese University of Hong Kong · Lanzhou University
AHD Agent: Agentic Reinforcement Learning for Automatic Heuristic Design
May 9, 2026Haoze Lv, Ning Lu, Ziang Zhou +1Agentic RL Automated Heuristic Design
Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation, Department of Computer Science and Engineering, Southern University of Science and Technology · Zhongguancun Academy · The Hong Kong University of Science and Technology
StraTA: Incentivizing Agentic Reinforcement Learning with Strategic Trajectory Abstraction
May 7, 2026Xiangyuan Xue, Yifan Zhou, Zidong Wang +5Agentic RL Hierarchical RL
1The Chinese University of Hong Kong · 2Shanghai Artificial Intelligence Laboratory · University of Georgia +2
Recursive Agent Optimization
May 7, 2026Apurva Gandhi, Satyaki Chakraborty, Xiangjun Wang +2Agentic RL Inference-Time Scaling
Carnegie Mellon University · Amazon AGI Labs
Safactory: A Scalable Agentic Infrastructure for Training Trustworthy Autonomous Intelligence
May 7, 2026Xinquan Chen, Zhenyun Yin, Shan He +38Agentic RL AI Agent Safety
Masked Diffusion Language Models are Strong and Steerable Text-Based World Models for Agentic RL
May 7, 2026Darshan DeshpandeLLM World Models World Models
Patronus AI

Jun 2, 2026, cs.LGJ/K move · Enter open · S save

Libra: Efficient Resource Management for Agentic RL Post-Training

Kaiwen Chen, Xin Tan, Jingzong Li, Zhi Zhou+5

The Chinese University of Hong Kong · The Hang Seng University of Hong Kong · Independent Researcher

Agentic RL Reinforcement Learning Distributed RL LLM Agent Training RL Post-Training

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Reinforcement learning (RL) has emerged as a standard post-training paradigm for shaping large language models (LLMs) into capable agents. In agentic RL, the rollout stage generates trajectories while invoking tools, producing long-tailed and non-stationary workloads that expose two fundamental challenges. First, due to the long-tailed response distribution, a small fraction of trajectories dominates rollout makespan.Second, rollout and training differ in their compute patterns, memory demands, and sensitivity to sequence length. As the policy evolves, shifts in the workload distribution further change their relative resource demands, making it difficult to maintain balanced execution across the two stages. We present Libra, an adaptive runtime for agentic RL post-training with two complementary components: (1) intra-stage scheduling via a Causality-Guided Bucket Scheduler that routes requests across execution buckets with different parallelism configurations, reducing delays from rollout stragglers; and (2) cross-stage coordination that dynamically reallocates workers between rollout and training as the workload changes. It moves workers between the two stages through a non-blocking protocol without interrupting ongoing training. Evaluated on a 48x NVIDIA A800 GPU cluster and a 160x Ascend 910B3 NPU cluster across three agentic benchmarks, Libra achieves up to 4.2x higher throughput and up to 2.7x faster reward convergence

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