Reinforcement Learning

Also known as RL

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144 papers in the last four weeks, up 243% on the four weeks before. 1.4% of all new papers.

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Transferable Delay-Aware Reinforcement Learning via Implicit Causal Graph Modeling
May 12, 2026Chenran Zhao, Dianxi Shi, Yaowen Zhang +2Causal Representation Learning Reinforcement Learning
College of Computer Science and Technology, National University of Defense Technology, Changsha, China · Institute of Military Transportation, Tianjin, China · Intelligent Game and Decision Lab (IGDL), Beijing, China
Delay-Empowered Causal Hierarchical Reinforcement Learning
May 12, 2026Chenran Zhao, Dianxi Shi, Haotian Wang +4Reinforcement Learning Hierarchical RL
College of Computer Science and Technology, National University of Defense Technology, Changsha, China · Intelligent Game and Decision Lab (IGDL), Beijing, China · School of Artificial Intelligence, Hebei University of Technology, Tianjin, China +1
Intrinsic Vicarious Conditioning for Deep Reinforcement Learning
May 12, 2026Rodney A Sanchez, Ferat Sahin, Alex Ororbia +1Reinforcement Learning Intrinsic Motivation
Department of Electrical and Microelectronic Engineering, Rochester Institute of Technology · Department of Computer Science, Rochester Institute of Technology
On the Importance of Multistability for Horizon Generalization in Reinforcement Learning
May 12, 2026Asad Bakija, Florent De Geeter, Julien Brandoit +2Dynamical Systems Reinforcement Learning
Dept. of Electrical Engineering and Computer Science · University of Liège · Liège, Belgium
Missing Old Logits in Asynchronous Agentic RL: Semantic Mismatch and Repair Methods for Off-Policy Correction
May 12, 2026Zhong Guan, Yongjian Guo, Haoran Sun +5Asynchronous RL Reinforcement Learning
Tianjin University · Tsinghua University · JDT AI Infra +1
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
Block-R1: Rethinking the Role of Block Size in Multi-domain Reinforcement Learning for Diffusion Large Language Models
May 12, 2026Yan Jiang, Ruihong Qiu, Zi HuangRL Benchmarks Reinforcement Learning
The University of Queensland
From Generic Correlation to Input-Specific Credit in On-Policy Self Distillation
May 12, 2026Guobin Shen, Lei Huang, Xiang Cheng +4Reinforcement Learning On-Policy Self-Distillation
Xiaohongshu Inc. · Institute of Automation, Chinese Academy of Sciences
CuSearch: Curriculum Rollout Sampling via Search Depth for Agentic RAG
May 12, 2026Jianghan Shen, Siqi Luo, Xinyu Cheng +6RL for Language Models Reinforcement Learning
1Nanjing University · 2Shanghai Artificial Intelligence Laboratory · University of Hong Kong +1
Learning Weakly Communicating Average-Reward CMDPs: Strong Duality and Improved Regret
May 12, 2026Kihyun Yu, Beomhan Baek, Dabeen LeeRegret Minimization in RL Markov Decision Processes
1KAIST · 2Seoul National University
Taming Extreme Tokens: Covariance-Aware GRPO with Gaussian-Kernel Advantage Reweighting
May 12, 2026Cheng Wang, Qin Liu, Wenxuan Zhou +1Reinforcement Learning RL for Language Model Reasoning
National University of Singapore · University of California, Davis · University of Southern California
Selective Off-Policy Reference Tuning with Plan Guidance
May 12, 2026Duc Anh Le, Tien-Phat Nguyen, Thien Huu Nguyen +2Reinforcement Learning RL for Language Model Reasoning
Independent Author · Hanoi University of Science and Technology, Hanoi, Vietnam · University of Oregon, Eugene, OR, USA +1
Understanding and Preventing Entropy Collapse in RLVR with On-Policy Entropy Flow Optimization
May 12, 2026Huimin Xu, Shuai Zhao, Xiaobao Wu +1Reinforcement Learning RL for Language Model Reasoning
Nanyang Technological University, Singapore · Shanghai Jiao Tong University, China · 3VinUniversity, Vietnam
Offline Policy Evaluation for Manipulation Policies via Discounted Liveness Formulation
May 12, 2026Hao Wang, Joshua Bowden, Colton Crosby +1RL for Robotics Reinforcement Learning
University of Southern California · Stanford University
Breaking $\textit{Winner-Takes-All}$ : Cooperative Policy Optimization Improves Diverse LLM Reasoning
May 12, 2026Haoxuan Chen, Tianming Liang, Wei-Shi Zheng +1Reinforcement Learning RL for Language Model Reasoning
1ISEE Lab, Sun Yat-sen University
fg-expo: Frontier-guided exploration-prioritized policy optimization via adaptive kl and gaussian curriculum
May 12, 2026Mingxiong Lin, Zhangquan Gong, Maowen Tang +6Reinforcement Learning RL for Language Model Reasoning
OPPO AI Center
Behavioral Mode Discovery for Fine-tuning Multimodal Generative Policies
May 12, 2026Alberta Longhini, David Emukpere, Jean-Michel Renders +1RL for Robotics Reinforcement Learning
Department of Computer Science, Stanford University, CA, USA
Quotient-Categorical Representations for Bellman-Compatible Average-Reward Distributional Reinforcement Learning
May 11, 2026Ege C. Kaya, Aliasghar Pourghani, Vijay Gupta +1Distributional RL Reinforcement Learning
Elmore Family School of Electrical and Computer Engineering Purdue University West Lafayette, IN 47906
Internalizing Curriculum Judgment for LLM Reinforcement Fine-Tuning
May 11, 2026Han Zheng, Yining Ma, Karthick Gunasekaran +4Reinforcement Learning Meta-Learning
MIT · Amazon AGI
Equivariant Reinforcement Learning for Clifford Quantum Circuit Synthesis
May 11, 2026Richie Yeung, Aleks Kissinger, Rob CornishReinforcement Learning Quantum Circuit Compilation
Department of Computer Science, University of Oxford · Quantinuum · College of Computing and Data Science, Nanyang Technological University, Singapore
RubricEM: Meta-RL with Rubric-guided Policy Decomposition beyond Verifiable Rewards
May 11, 2026Gaotang Li, Bhavana Dalvi Mishra, Zifeng Wang +9Reinforcement Learning Rubric-Based RL
University of Illinois Urbana-Champaign · Google Cloud AI Research
UniSteer: Unified Noise Steering for Efficient Human-Guided VLA Adaptation
May 11, 2026Junjie Lu, Xinyao Qin, Yuhua Jiang +6RL for Robotics Robot Policy Adaptation
University of Technology Sydney · Work conducted at Microsoft Research. · Tsinghua University +1
Policy Gradient Methods for Non-Markovian Reinforcement Learning
May 11, 2026Avik Kar, Siddharth Chandak, Rahul Singh +4Reinforcement Learning Policy Gradient Methods
Department of Computer Science and Automation, Indian Institute of Science, Bengaluru, India. · Department of Electrical Engineering, Stanford University, Stanford, CA, USA. · Department of Electrical and Electronics Engineering, Nanyang Technological University, Singapore. +1
New AI-Driven Tools for Enhancing Campus Well-being: A Prevention and Intervention Approach
May 11, 2026Jinwen TangReinforcement Learning Depression Detection
University of Missouri-Columbia[cs.AI]
Natural Policy Gradient as Doubly Smoothed Policy Iteration: A Bellman-Operator Framework
May 11, 2026Phalguni Nanda, Zaiwei ChenPolicy Gradient Reinforcement Learning
Edwardson School of Industrial Engineering, Purdue University
Evolving-RL: End-to-End Optimization of Experience-Driven Self-Evolving Capability within Agents
May 11, 2026Zhiyuan Fan, Wenwei Jin, Feng Zhang +4Reinforcement Learning Language Model Self-Improvement
1Xiaohongshu Inc. · School of Computer Science, Peking University
Balancing Efficiency and Fairness in Traffic Light Control through Deep Reinforcement Learning
May 11, 2026Matteo Cederle, Giacomo Scatto, Gian Antonio SustoReinforcement Learning Intelligent Transportation Systems
University of Padova, Italy
EFGCL: Learning Dynamic Motion through Spotting-Inspired External Force Guided Curriculum Learning
May 11, 2026Keita Yoneda, Kento Kawaharazuka, Kei OkadaReinforcement Learning Whole-Body Control
Department of Mechano-Informatics, Graduate School of Information Science and Technology, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan · AI Center, Graduate School of Information Science and Technology, The University of Tokyo, Japan
expo: Exploration-prioritized policy optimization via adaptive kl regulation and gaussian curriculum sampling
May 11, 2026Mingxiong Lin, Zhangquan Gong, Maowen Tang +6Reinforcement Learning KL-Regularized RL
OPPO AI Center
Verifier-Free RL for LLMs via Intrinsic Gradient-Norm Reward
May 11, 2026Xuexiang Wen, Hang Yu, Linchao Zhu +1Intrinsic Reward Methods Reinforcement Learning
1Zhejiang University · 2Ant Group

May 12, 2026, cs.LGJ/K move · Enter open · S save

Transferable Delay-Aware Reinforcement Learning via Implicit Causal Graph Modeling

Chenran Zhao, Dianxi Shi, Yaowen Zhang, Chunping Qiu+1

College of Computer Science and Technology, National University of Defense Technology, Changsha, China · Institute of Military Transportation, Tianjin, China · Intelligent Game and Decision Lab (IGDL), Beijing, China

Causal Representation Learning Reinforcement Learning Model-Based RL

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Random delays weaken the temporal correspondence between actions and subsequent state feedback, making it difficult for agents to identify the true propagation process of action effects. In cross-task scenarios, changes in task objectives and reward formulations further reduce the reusability of previously acquired task knowledge. To address this problem, this paper proposes a transferable delay-aware reinforcement learning method based on implicit causal graph modeling. The proposed method uses a field-node encoder to represent high-dimensional observations as latent states with node-level semantics, and employs a message-passing mechanism to characterize dynamic causal dependencies among nodes, thereby learning transferable structured representations and environment dynamics knowledge. On this basis, imagination-driven behavior learning and planning are incorporated to optimize policies in the latent space, enabling cross-task knowledge transfer and rapid adaptation. Experimental results show that the proposed method outperforms baseline methods on DMC continuous control tasks with random delays. Cross-task transfer experiments further demonstrate that the learned structured representations and dynamics knowledge can be effectively transferred to new tasks and significantly accelerate policy adaptation.

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Latest papers 1,147