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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Latest papers 1,147

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Angel or Demon: Investigating the Plasticity Interventions' Impact on Backdoor Threats in Deep Reinforcement Learning
May 14, 2026Oubo Ma, Ruixiao Lin, Yang Dai +4Reinforcement Learning Backdoor Attacks
1Zhejiang University · 2National University of Defense Technol · 3Xi’an Jiaotong University
Fully Dynamic Rebalancing in Dockless Bike-Sharing Systems via Deep Reinforcement Learning
May 14, 2026Edoardo Scarpel, Alberto Pettena, Matteo Cederle +3RL Control Reinforcement Learning
University of Padua, via Gradenigo 6/B, 35131, Padua, Italy
ROAD: Adaptive Data Mixing for Offline-to-Online Reinforcement Learning via Bi-Level Optimization
May 14, 2026Letian Yang, Xu Liu, Yiqiang Lu +3Reinforcement Learning Offline-To-Online RL
Shanghai Jiao Tong University, Shanghai, China · Ant Group, Shanghai, China
COLLATOR: Compositional Multi-Agent Orchestration with Counterfactual Reinforcement Learning
May 14, 2026Xudong Chen, Yixin Liu, Hua Wei +1Multi-Agent System Optimization Multi-Agent Orchestration
A Unified Knowledge Embedded Reinforcement Learning-based Framework for Generalized Capacitated Vehicle Routing Problems
May 14, 2026Wen Wang, Xiangchen Wu, Liang Wang +2Reinforcement Learning Vehicle Routing
Nanjing University
Learning to Build the Environment: Self-Evolving Reasoning RL via Verifiable Environment Synthesis
May 14, 2026Yucheng Shi, Zhenwen Liang, Kishan Panaganti +3Reinforcement Learning RL for Language Model Reasoning
Tencent HY LLM
Reinforcement Learning with Semantic Rewards Enables Low-Resource Language Expansion without Alignment Tax
May 14, 2026Zeli Su, Ziyin Zhang, Zhou Liu +7Reinforcement Learning Low-Resource MT
Minzu University of China · Ant Group · Shanghai Jiao Tong University +4
Matrix-Space Reinforcement Learning for Reusing Local Transition Geometry
May 14, 2026Zuyuan Zhang, Carlee Joe-Wong, Tian LanReinforcement Learning Trajectory Representation Learning
The George Washington University · Carnegie Mellon University
Policy Optimization in Hybrid Discrete-Continuous Action Spaces via Mixed Gradients
May 14, 2026Matias Alvo, Daniel Russo, Yash KanoriaRL Control Reinforcement Learning
Graduate School of Business Columbia University
CreFlow: Corrective Reflow for Sparse-Reward Embodied Video Diffusion RL
May 14, 2026Zhenyang Ni, Yijiang Li, Ruochen Jiao +7Video Diffusion Models Reinforcement Learning
Northwestern University · University of California, San Diego · University of Oxford
Diagnosing Training Inference Mismatch in LLM Reinforcement Learning via a Zero-Mismatch Reference
May 14, 2026Tianle Zhong, Neiwen Ling, Yifan Pi +5Reinforcement Learning LLM Inference
ByteDance · The University of Virginia
R2R2: Robust Representation for Intensive Experience Reuse via Redundancy Reduction in Self-Predictive Learning
May 13, 2026Sanghyeob Song, Donghyeok Lee, Jinsik Kim +1Reinforcement Learning Self-Supervised Learning
Interdisciplinary Program in Artificial Intelligence, Seoul National University · Samsung Electro-Mechanics, Republic of Korea · Department of Electrical and Computer Engineering, Seoul National University
Tight Sample Complexity Bounds for Entropic Best Policy Identification
May 13, 2026Amer Essakine, Claire VernadeReinforcement Learning Risk-Sensitive RL
ENS Paris Saclay · University of Technology Nuremberg
Self-Supervised On-Policy Reinforcement Learning via Contrastive Proximal Policy Optimisation
May 13, 2026Asim Osman, Sasha Abramowitz, Mark Bergh +13Reinforcement Learning Contrastive RL
InstaDeep, AIMS · InstaDeep, University of Stellenbosch
CA2: Code-Aware Agent for Automated Game Testing
May 13, 2026Valliappan Chidambaram Adaikkappan, Vincent Martineau, Joshua Romoff +1Automated Software Testing Reinforcement Learning
† McGill University · ⋄Mila Quebec AI Institute · ‡ Ubisoft
Q-Flow: Stable and Expressive Reinforcement Learning with Flow-Based Policy
May 13, 2026JaeHyeok Doo, Byeongguk Jeon, Seonghyeon Ye +2Reinforcement Learning Offline RL
1KAIST
D-VLA: A High-Concurrency Distributed Asynchronous Reinforcement Learning Framework for Vision-Language-Action Models
May 13, 2026Yucheng Guo, Yongjian Guo, Zhong Guan +9Reinforcement Learning Communication-Efficient Distributed Training
JDT AI Infra · Tsinghua University · Tianjin University +2
GAGPO: Generalized Advantage Grouped Policy Optimization
May 13, 2026Siyuan Zhu, Chao Yu, Rongxin Yang +4Reinforcement Learning Group Relative Policy Optimization
School of Computer Science and Engineering, Sun Yat-sen University · Meituan
Switching Successor Measures for Hierarchical Zero-shot Reinforcement Learning
May 13, 2026Stefan Stojanovic, Alexandre ProutiereRepresentation Learning Reinforcement Learning
KTH, Stockholm, Sweden · KTH, Digital Futures, Stockholm, Sweden
Offline Two-Player Zero-Sum Markov Games with KL Regularization
May 13, 2026Claire Chen, Yuheng Zhang, Xinyu Liu +3Nash Equilibrium Reinforcement Learning
1California Institute of Technology. · University of Illinois Urbana-Champaign. · University of Virginia. +2
Safe Continual Reinforcement Learning under Nonstationarity via Adaptive Safety Constraints
May 13, 2026Timofey TomashevskiyNon-Stationary RL Reinforcement Learning
McMaster Centre for Software Certification Department of Computing and Software McMaster University, Canada
AIS: Adaptive Importance Sampling for Quantized RL
May 13, 2026Jiajun Zhou, Wei Shao, Lingchao Zheng +2RL for Language Models Reinforcement Learning
Huawei · The University of Hong Kong
Quantifying Potential Observation Missingness in Inverse Reinforcement Learning
May 12, 2026Leo Benac, Abhishek Sharma, Alihan Huyuk +1Reinforcement Learning Healthcare
School of Engineering and Applied Sciences Harvard University
ODRPO: Ordinal Decompositions of Discrete Rewards for Robust Policy Optimization
May 12, 2026Nirmal Patel, Fei Wang, Inderjit S. DhillonRL for Language Models Reinforcement Learning
University of Texas at Austin · Google
Robust Instruction Compliance in Cooperative Multi-Agent Reinforcement Learning
May 12, 2026Wo Wei Lin, Ethan Rathbun, Enrico Marchesini +1Reinforcement Learning Robust RL
Department of Computer Sciences Northeastern University United States · Department of Computer Sciences Massachusetts Institute of Technology United States
Plan Before You Trade: Inference-Time Optimization for RL Trading Agents
May 12, 2026Eun Go, Rohan Deb, Arindam BanerjeeReinforcement Learning Inference-Time Optimization
Siebel School of Computing and Data Science University of Illinois Urbana-Champaign
Beyond GRPO and On-Policy Distillation: An Empirical Sparse-to-Dense Reward Principle for Language-Model Post-Training
May 12, 2026Yuanda Xu, Hejian Sang, Zhengze Zhou +3Reinforcement Learning RL for Language Model Reasoning
Reward Hacking in Rubric-Based Reinforcement Learning
May 12, 2026Anas Mahmoud, MohammadHossein Rezaei, Zihao Wang +3Reward Hacking Reinforcement Learning
Scale AI
Towards Affordable Energy: A Gymnasium Environment for Electric Utility Demand-Response Programs
May 12, 2026Jose E. Aguilar Escamilla, Lingdong Zhou, Xiangqi Zhu +1RL Benchmarks Reinforcement Learning
Department of Electrical Engineering and Computer Science, Oregon State University, USA
Discrete Flow Matching for Offline-to-Online Reinforcement Learning
May 12, 2026Fairoz Nower Khan, Nabuat Zaman Nahim, Peizhong JuFlow Matching Reinforcement Learning
Department of Computer Science, University of Kentucky

May 14, 2026, cs.LGJ/K move · Enter open · S save

Angel or Demon: Investigating the Plasticity Interventions' Impact on Backdoor Threats in Deep Reinforcement Learning

Oubo Ma, Ruixiao Lin, Yang Dai, Jiahao Chen+3

1Zhejiang University · 2National University of Defense Technol · 3Xi’an Jiaotong University

Reinforcement Learning Backdoor Attacks Backdoor Detection Robust RL

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Extensive research has highlighted the severe threats posed by backdoor attacks to deep reinforcement learning (DRL). However, prior studies primarily focus on vanilla scenarios, while plasticity interventions have emerged as indispensable built-in components of modern DRL agents. Despite their effectiveness in mitigating plasticity loss, the impact of these interventions on DRL backdoor vulnerabilities remains underexplored, and this lack of systematic investigation poses risks in practical DRL deployments. To bridge this gap, we empirically study 14,664 cases integrating representative interventions and attack scenarios. We find that only one intervention (i.e., SAM) exacerbates backdoor threats, while other interventions mitigate them. Pathological analysis identifies that the exacerbation is attributed to backdoor gradient amplification, while the mitigation stems from activation pathway disruption and representation space compression. From these findings, we derive two novel insights: (1) a conceptual framework SCC for robust backdoor injection that deconstructs the mechanistic interplay between interventions and backdoors in DRL, and (2) abnormal loss landscape sharpness as a key indicator for DRL backdoor detection.

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Latest papers 1,147