Reinforcement Learning
Learning through interaction and rewards
Top Papers
Eureka: Human-Level Reward Design via Coding Large Language Models
Yecheng Jason Ma, William Liang, Guanzhi Wang et al.
Self-Play Preference Optimization for Language Model Alignment
Yue Wu, Zhiqing Sun, Rina Hughes et al.
VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning
Haozhe Wang, Chao Qu, Zuming Huang et al.
ToolRL: Reward is All Tool Learning Needs
Cheng Qian, Emre Can Acikgoz, Qi He et al.
HelpSteer2-Preference: Complementing Ratings with Preferences
Zhilin Wang, Alexander Bukharin, Olivier Delalleau et al.
The Surprising Effectiveness of Negative Reinforcement in LLM Reasoning
Xinyu Zhu, Mengzhou Xia, Zhepei Wei et al.
Learning to Act without Actions
Dominik Schmidt, Minqi Jiang
BadCLIP: Trigger-Aware Prompt Learning for Backdoor Attacks on CLIP
Jiawang Bai, Kuofeng Gao, Shaobo Min et al.
LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Models
Marwa Abdulhai, Isadora White, Charlie Snell et al.
Perception-R1: Pioneering Perception Policy with Reinforcement Learning
En Yu, Kangheng Lin, Liang Zhao et al.
CLoSD: Closing the Loop between Simulation and Diffusion for multi-task character control
Guy Tevet, Sigal Raab, Setareh Cohan et al.
Duolando: Follower GPT with Off-Policy Reinforcement Learning for Dance Accompaniment
Siyao Li, Tianpei Gu, Zhitao Yang et al.
OMNI-EPIC: Open-endedness via Models of human Notions of Interestingness with Environments Programmed in Code
Maxence Faldor, Jenny Zhang, Antoine Cully et al.
RRM: Robust Reward Model Training Mitigates Reward Hacking
Tianqi Liu, Wei Xiong, Jie Ren et al.
Diffusion Reward: Learning Rewards via Conditional Video Diffusion
Tao Huang, Guangqi Jiang, Yanjie Ze et al.
On Targeted Manipulation and Deception when Optimizing LLMs for User Feedback
Marcus Williams, Micah Carroll, Adhyyan Narang et al.
Dual RL: Unification and New Methods for Reinforcement and Imitation Learning
Harshit Sikchi, Qinqing Zheng, Amy Zhang et al.
Reasoning Gym: Reasoning Environments for Reinforcement Learning with Verifiable Rewards
Zafir Stojanovski, Oliver Stanley, Joe Sharratt et al.
CPPO: Continual Learning for Reinforcement Learning with Human Feedback
Han Zhang, Yu Lei, Lin Gui et al.
Dispider: Enabling Video LLMs with Active Real-Time Interaction via Disentangled Perception, Decision, and Reaction
Rui Qian, Shuangrui Ding, Xiaoyi Dong et al.
Enhancing Diffusion Models with Text-Encoder Reinforcement Learning
Chaofeng Chen, Annan Wang, Haoning Wu et al.
Entity-Centric Reinforcement Learning for Object Manipulation from Pixels
Dan Haramati, Tal Daniel, Aviv Tamar
RLIF: Interactive Imitation Learning as Reinforcement Learning
Jianlan Luo, Perry Dong, Yuexiang Zhai et al.
ACT: Empowering Decision Transformer with Dynamic Programming via Advantage Conditioning
Chen-Xiao Gao, Chenyang Wu, Mingjun Cao et al.
Revisiting Plasticity in Visual Reinforcement Learning: Data, Modules and Training Stages
Guozheng Ma, Lu Li, Sen Zhang et al.
AlignSAM: Aligning Segment Anything Model to Open Context via Reinforcement Learning
Duojun Huang, Xinyu Xiong, Jie Ma et al.
Reward Guided Latent Consistency Distillation
William Wang, Jiachen Li, Weixi Feng et al.
Latent Reward: LLM-Empowered Credit Assignment in Episodic Reinforcement Learning
Yun Qu, Yuhang Jiang, Boyuan Wang et al.
Improving Agent Behaviors with RL Fine-tuning for Autonomous Driving
Zhenghao Peng, Wenjie Luo, Yiren Lu et al.
Domain Randomization via Entropy Maximization
Gabriele Tiboni, Pascal Klink, Jan Peters et al.
DiffAIL: Diffusion Adversarial Imitation Learning
Bingzheng Wang, Guoqiang Wu, Teng Pang et al.
ReinboT: Amplifying Robot Visual-Language Manipulation with Reinforcement Learning
Hongyin Zhang, Zifeng Zhuang, Han Zhao et al.
Towards Better Alignment: Training Diffusion Models with Reinforcement Learning Against Sparse Rewards
Zijing Hu, Fengda Zhang, Long Chen et al.
Online Preference Alignment for Language Models via Count-based Exploration
Chenjia Bai, Yang Zhang, Shuang Qiu et al.
SeRL: Self-play Reinforcement Learning for Large Language Models with Limited Data
Wenkai Fang, Shunyu Liu, Yang Zhou et al.
Raw2Drive: Reinforcement Learning with Aligned World Models for End-to-End Autonomous Driving (in CARLA v2)
Zhenjie Yang, Xiaosong Jia, Qifeng Li et al.
SELF-EVOLVED REWARD LEARNING FOR LLMS
Chenghua Huang, Zhizhen Fan, Lu Wang et al.
Cross-Embodiment Dexterous Grasping with Reinforcement Learning
Haoqi Yuan, Bohan Zhou, Yuhui Fu et al.
MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization
Bhavya, Stelian Coros, Andreas Krause et al.
ThinkBot: Embodied Instruction Following with Thought Chain Reasoning
Guanxing Lu, Ziwei Wang, Changliu Liu et al.
RGMComm: Return Gap Minimization via Discrete Communications in Multi-Agent Reinforcement Learning
Jingdi Chen, Tian Lan, Carlee Joe-Wong
Learning Optimal Advantage from Preferences and Mistaking It for Reward
W Bradley Knox, Stephane Hatgis-Kessell, Sigurdur Orn Adalgeirsson et al.
Ready-to-React: Online Reaction Policy for Two-Character Interaction Generation
Zhi Cen, Huaijin Pi, Sida Peng et al.
Simulating Human-like Daily Activities with Desire-driven Autonomy
Yiding Wang, Yuxuan Chen, Fangwei Zhong et al.
Reward-Consistent Dynamics Models are Strongly Generalizable for Offline Reinforcement Learning
Fan-Ming Luo, Tian Xu, Xingchen Cao et al.
SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning
Xiao Liang, Zhong-Zhi Li, Yeyun Gong et al.
Regressing the Relative Future: Efficient Policy Optimization for Multi-turn RLHF
Zhaolin Gao, Wenhao Zhan, Jonathan Chang et al.
Reinforcement Learning Friendly Vision-Language Model for Minecraft
Haobin Jiang, Junpeng Yue, Hao Luo et al.
PILAF: Optimal Human Preference Sampling for Reward Modeling
Yunzhen Feng, Ariel Kwiatkowski, Kunhao Zheng et al.
Rating-Based Reinforcement Learning
Devin White, Mingkang Wu, Ellen Novoseller et al.
Asymmetric REINFORCE for off-Policy Reinforcement Learning: Balancing positive and negative rewards
Charles Arnal, Gaëtan Narozniak, Vivien Cabannes et al.
Scaling Autonomous Agents via Automatic Reward Modeling And Planning
Zhenfang Chen, Delin Chen, Rui Sun et al.
AdaManip: Adaptive Articulated Object Manipulation Environments and Policy Learning
Yuanfei Wang, Xiaojie Zhang, Ruihai Wu et al.
Enhancing Personalized Multi-Turn Dialogue with Curiosity Reward
Yanming Wan, Jiaxing Wu, Marwa Abdulhai et al.
RAT: Adversarial Attacks on Deep Reinforcement Agents for Targeted Behaviors
Fengshuo Bai, Runze Liu, Yali Du et al.
ConcaveQ: Non-monotonic Value Function Factorization via Concave Representations in Deep Multi-Agent Reinforcement Learning
Huiqun Li, Hanhan Zhou, Yifei Zou et al.
Multi-Teacher Knowledge Distillation with Reinforcement Learning for Visual Recognition
Chuanguang Yang, XinQiang Yu, Han Yang et al.
MetaRLEC: Meta-Reinforcement Learning for Discovery of Brain Effective Connectivity
Zuozhen Zhang, Junzhong Ji, Jinduo Liu
ROCKET-1: Mastering Open-World Interaction with Visual-Temporal Context Prompting
Shaofei Cai, Zihao Wang, Kewei Lian et al.
Open the Black Box: Step-based Policy Updates for Temporally-Correlated Episodic Reinforcement Learning
Ge Li, Hongyi Zhou, Dominik Roth et al.
Smart Help: Strategic Opponent Modeling for Proactive and Adaptive Robot Assistance in Households
Zhihao Cao, ZiDong Wang, Siwen Xie et al.
Benchmarking Multimodal CoT Reward Model Stepwise by Visual Program
Minghe Gao, Xuqi Liu, Zhongqi Yue et al.
Open-World Reinforcement Learning over Long Short-Term Imagination
Jiajian Li, Qi Wang, Yunbo Wang et al.
ConfigX: Modular Configuration for Evolutionary Algorithms via Multitask Reinforcement Learning
Hongshu Guo, Zeyuan Ma, Jiacheng Chen et al.
Strategy Coopetition Explains the Emergence and Transience of In-Context Learning
Aaditya Singh, Ted Moskovitz, Sara Dragutinović et al.
GENTEEL-NEGOTIATOR: LLM-Enhanced Mixture-of-Expert-Based Reinforcement Learning Approach for Polite Negotiation Dialogue
Priyanshu Priya, Rishikant Chigrupaatii, Mauajama Firdaus et al.
Bootstrapping Language-Guided Navigation Learning with Self-Refining Data Flywheel
Zun Wang, Jialu Li, Yicong Hong et al.
SAM-R1: Leveraging SAM for Reward Feedback in Multimodal Segmentation via Reinforcement Learning
Jiaqi Huang, Zunnan Xu, Jun Zhou et al.
DreamSmooth: Improving Model-based Reinforcement Learning via Reward Smoothing
Vint Lee, Pieter Abbeel, Youngwoon Lee
Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization
Daniel Palenicek, Florian Vogt, Joe Watson et al.
Web-Shepherd: Advancing PRMs for Reinforcing Web Agents
Hyungjoo Chae, Seonghwan Kim, Junhee Cho et al.
Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization
Zongkai Liu, Qian Lin, Chao Yu et al.
Social Reward: Evaluating and Enhancing Generative AI through Million-User Feedback from an Online Creative Community
Arman Isajanyan, Artur Shatveryan, David Kocharian et al.
REvolve: Reward Evolution with Large Language Models using Human Feedback
RISHI HAZRA, Alkis Sygkounas, Andreas Persson et al.
DisCO: Reinforcing Large Reasoning Models with Discriminative Constrained Optimization
Gang Li, Ming Lin, Tomer Galanti et al.
Bidirectional Progressive Transformer for Interaction Intention Anticipation
Zichen Zhang, Hongchen Luo, Wei Zhai et al.
Direct Alignment with Heterogeneous Preferences
Ali Shirali, Arash Nasr-Esfahany, Abdullah Alomar et al.
SafeVLA: Towards Safety Alignment of Vision-Language-Action Model via Constrained Learning
Borong Zhang, Yuhao Zhang, Jiaming Ji et al.
Distilling Reinforcement Learning Algorithms for In-Context Model-Based Planning
Jaehyeon Son, Soochan Lee, Gunhee Kim
DrS: Learning Reusable Dense Rewards for Multi-Stage Tasks
Tongzhou Mu, Minghua Liu, Hao Su
Enhancing Rating-Based Reinforcement Learning to Effectively Leverage Feedback from Large Vision-Language Models
Minh-Tung Luu, Younghwan Lee, Donghoon Lee et al.
The Bandit Whisperer: Communication Learning for Restless Bandits
Yunfan Zhao, Tonghan Wang, Dheeraj Mysore Nagaraj et al.
WHAT MAKES MATH PROBLEMS HARD FOR REINFORCEMENT LEARNING: A CASE STUDY
Ali Shehper, Anibal Medina-Mardones, Lucas Fagan et al.
TempSamp-R1: Effective Temporal Sampling with Reinforcement Fine-Tuning for Video LLMs
Yunheng Li, Jing Cheng, Shaoyong Jia et al.
Bidirectional Decoding: Improving Action Chunking via Guided Test-Time Sampling
Yuejiang Liu, Jubayer Hamid, Annie Xie et al.
Advantage Alignment Algorithms
Juan Duque, Milad Aghajohari, Timotheus Cooijmans et al.
When Maximum Entropy Misleads Policy Optimization
Ruipeng Zhang, Ya-Chien Chang, Sicun Gao
InteractAnything: Zero-shot Human Object Interaction Synthesis via LLM Feedback and Object Affordance Parsing
Jinlu Zhang, Yixin Chen, Zan Wang et al.
Inverse Reinforcement Learning by Estimating Expertise of Demonstrators
Mark Beliaev, Ramtin Pedarsani
REVECA: Adaptive Planning and Trajectory-Based Validation in Cooperative Language Agents Using Information Relevance and Relative Proximity
SeungWon Seo, SeongRae Noh, Junhyeok Lee et al.
The Curse of Diversity in Ensemble-Based Exploration
Zhixuan Lin, Pierluca D'Oro, Evgenii Nikishin et al.
Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching
Arnav Kumar Jain, Harley Wiltzer, Jesse Farebrother et al.
Enabling Realtime Reinforcement Learning at Scale with Staggered Asynchronous Inference
Matt Riemer, Gopeshh Raaj Subbaraj, Glen Berseth et al.
Compliant Residual DAgger: Improving Real-World Contact-Rich Manipulation with Human Corrections
Xiaomeng Xu, Yifan Hou, Zeyi Liu et al.
Explore 3D Dance Generation via Reward Model from Automatically-Ranked Demonstrations
Zilin Wang, Haolin Zhuang, Lu Li et al.
PRIMAL: Physically Reactive and Interactive Motor Model for Avatar Learning
Yan Zhang, Yao Feng, Alpár Cseke et al.
Neural Interactive Proofs
Lewis Hammond, Sam Adam-Day
Unsupervised Object Interaction Learning with Counterfactual Dynamics Models
Jongwook Choi, Sungtae Lee, Xinyu Wang et al.
Noise-Resilient Symbolic Regression with Dynamic Gating Reinforcement Learning
Chenglu Sun, Shuo Shen, Wenzhi Tao et al.
Real-Time Recurrent Reinforcement Learning
Julian Lemmel, Radu Grosu