Reinforcement Learning

ICLR 2024arXiv:2310.12773

#2

Safe RLHF: Safe Reinforcement Learning from Human Feedback

Juntao Dai, Xuehai Pan, Ruiyang Sun et al.

567

ICML 2024arXiv:2309.00267

#3

RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback

Harrison Lee, Samrat Phatale, Hassan Mansoor et al.

reinforcement learning from human feedbackreinforcement learning from ai feedbackreward model traininglarge language model alignment+4

527

ICML 2024arXiv:2401.10020

#4

Self-Rewarding Language Models

Weizhe Yuan, Richard Yuanzhe Pang, Kyunghyun Cho et al.

self-rewarding language modelsllm-as-a-judge promptingiterative dpo traininginstruction following ability+4

497

ICLR 2024arXiv:2310.12931

#5

Eureka: Human-Level Reward Design via Coding Large Language Models

Yecheng Jason Ma, William Liang, Guanzhi Wang et al.

491

ICML 2024arXiv:2312.11456

#6

Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-constraint

Wei Xiong, Hanze Dong, Chenlu Ye et al.

reinforcement learning from human feedbackreverse-kl regularizationcontextual bandit formulationdirect preference optimization+4

312

ICLR 2025arXiv:2405.00675

#7

Self-Play Preference Optimization for Language Model Alignment

Yue Wu, Zhiqing Sun, Rina Hughes et al.

221

ICML 2024arXiv:2312.00886

#8

Nash Learning from Human Feedback

REMI MUNOS, Michal Valko, Daniele Calandriello et al.

reinforcement learning from human feedbackreward model learningpreference modelingnash equilibrium+4

195

NEURIPS 2025arXiv:2504.08837

#9

VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning

Haozhe Wang, Chao Qu, Zuming Huang et al.

vision-language modelsreinforcement learningslow-thinking systemsmultimodal reasoning+4

183

NEURIPS 2025arXiv:2504.13958

#10

ToolRL: Reward is All Tool Learning Needs

Cheng Qian, Emre Can Acikgoz, Qi He et al.

178

ICML 2024arXiv:2401.04056

#11

A Minimaximalist Approach to Reinforcement Learning from Human Feedback

Gokul Swamy, Christoph Dann, Rahul Kidambi et al.

reinforcement learning from human feedbackpreference optimizationself-play algorithmsminimax winner+4

139

ICML 2024arXiv:2310.18940

#12

Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game

Zelai Xu, Chao Yu, Fei Fang et al.

reinforcement learninglarge language modelsstrategic decision-makingsocial deduction games+4

136

ICML 2024arXiv:2402.10207

#13

Rewards-in-Context: Multi-objective Alignment of Foundation Models with Dynamic Preference Adjustment

Rui Yang, Xiaoman Pan, Feng Luo et al.

multi-objective alignmenthuman preference alignmentreinforcement learning fine-tuningsupervised fine-tuning+4

125

ICML 2024arXiv:2402.03681

#14

RL-VLM-F: Reinforcement Learning from Vision Language Foundation Model Feedback

Yufei Wang, Zhanyi Sun, Jesse Zhang et al.

reward engineeringvision language modelspreference learningautonomous manipulation+4

119

ICLR 2025arXiv:2410.01257

#15

HelpSteer2-Preference: Complementing Ratings with Preferences

Zhilin Wang, Alexander Bukharin, Olivier Delalleau et al.

reward modelingbradley-terry modelpreference annotationinstruction following alignment+4

112

ICLR 2024arXiv:2309.11489

#16

Text2Reward: Reward Shaping with Language Models for Reinforcement Learning

Tianbao Xie, Siheng Zhao, Chen Henry Wu et al.

111

ICML 2025arXiv:2410.02089

#17

RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning

Jonas Gehring, Kunhao Zheng, Jade Copet et al.

91

NEURIPS 2025arXiv:2506.01347

#18

The Surprising Effectiveness of Negative Reinforcement in LLM Reasoning

Xinyu Zhu, Mengzhou Xia, Zhepei Wei et al.

reinforcement learningmathematical reasoninglanguage modelspolicy gradients+4

89

ICML 2024arXiv:2402.08925

#19

MaxMin-RLHF: Alignment with Diverse Human Preferences

Souradip Chakraborty, Jiahao Qiu, Hui Yuan et al.

reinforcement learning from human feedbackreward model diversityhuman preference alignmentmixture of reward models+3

88

ICLR 2024arXiv:2312.10812

#20

Learning to Act without Actions

Dominik Schmidt, Minqi Jiang

78

ICLR 2025arXiv:2501.10893

#21

Learn-by-interact: A Data-Centric Framework For Self-Adaptive Agents in Realistic Environments

Hongjin SU, Ruoxi Sun, Jinsung Yoon et al.

69

ICML 2025arXiv:2311.18232

#22

LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Models

Marwa Abdulhai, Isadora White, Charlie Snell et al.

67

ICML 2024arXiv:2402.00782

#23

Dense Reward for Free in Reinforcement Learning from Human Feedback

Alexander Chan, Hao Sun, Samuel Holt et al.

reinforcement learning from human feedbackreward model attentionpotential-based reward shapingsparse reward problem+3

65

NEURIPS 2025arXiv:2504.07954

#24

Perception-R1: Pioneering Perception Policy with Reinforcement Learning

En Yu, Kangheng Lin, Liang Zhao et al.

62

ICML 2024arXiv:2402.06627

#25

Feedback Loops With Language Models Drive In-Context Reward Hacking

Alexander Pan, Erik Jones, Meena Jagadeesan et al.

feedback loopslanguage model agentsreward hackingin-context learning+3

60

CVPR 2024arXiv:2312.09238

#26

Auto MC-Reward: Automated Dense Reward Design with Large Language Models for Minecraft

Hao Li, Xue Yang, Zhaokai Wang et al.

58

ICLR 2024arXiv:2310.05910

#27

SALMON: Self-Alignment with Instructable Reward Models

Zhiqing Sun, Yikang Shen, Hongxin Zhang et al.

55

NEURIPS 2025arXiv:2503.15477

#28

Training Diffusion Models Towards Diverse Image Generation with Reinforcement Learning

Zichen Miao, Jiang Wang, Ze Wang et al.

What Makes a Reward Model a Good Teacher? An Optimization Perspective

Noam Razin, Zixuan Wang, Hubert Strauss et al.

53

ICML 2024arXiv:2401.16335

#30

Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF

Banghua Zhu, Michael Jordan, Jiantao Jiao

reward model learninghuman feedback alignmentreward overoptimizationiterative data smoothing+3

48

ICLR 2024arXiv:2310.19668

#31

DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization

Guowei Xu, Ruijie Zheng, Yongyuan Liang et al.

46

ECCV 2024arXiv:2312.14134

#32

Diffusion Reward: Learning Rewards via Conditional Video Diffusion

Tao Huang, Guangqi Jiang, Yanjie Ze et al.

reward learningexpert video conditioningconditional video diffusionvisual reinforcement learning+4

44

ICLR 2025arXiv:2411.02306

#33

On Targeted Manipulation and Deception when Optimizing LLMs for User Feedback

Marcus Williams, Micah Carroll, Adhyyan Narang et al.

reinforcement learninguser feedback optimizationtargeted manipulationdeceptive tactics+4

43

ICLR 2024arXiv:2302.08560

#34

Dual RL: Unification and New Methods for Reinforcement and Imitation Learning

Harshit Sikchi, Qinqing Zheng, Amy Zhang et al.

41

ICML 2024arXiv:2402.17257

#35

RIME: Robust Preference-based Reinforcement Learning with Noisy Preferences

Jie Cheng, Gang Xiong, Xingyuan Dai et al.

preference-based reinforcement learningnoisy preference learningrobust reward learningsample selection discriminator+3

35

ICLR 2025arXiv:2407.00617

#36

Iterative Nash Policy Optimization: Aligning LLMs with General Preferences via No-Regret Learning

Yuheng Zhang, Dian Yu, Baolin Peng et al.

reinforcement learning human feedbackpreference modelinggame-theoretic alignmentnash policy optimization+4

34

ICLR 2024arXiv:2305.18246

#37

Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo

Haque Ishfaq, Qingfeng Lan, Pan Xu et al.

33

NEURIPS 2025arXiv:2507.18624

#38

CPPO: Continual Learning for Reinforcement Learning with Human Feedback

Han Zhang, Yu Lei, Lin Gui et al.

Checklists Are Better Than Reward Models For Aligning Language Models

Vijay Viswanathan, Yanchao Sun, Xiang Kong et al.

reinforcement learninginstruction followingchecklist feedbackai judges+3

32

NEURIPS 2025arXiv:2507.07969

#40

Reinforcement Learning with Action Chunking

Qiyang Li, Zhiyuan (Paul) Zhou, Sergey Levine

29

NEURIPS 2025arXiv:2506.01300

#41

ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding

Yiyang Zhou, Yangfan He, Yaofeng Su et al.

video understandingreward-driven agentsmulti-agent frameworkvision-language models+4

29

ICML 2024arXiv:2402.08848

#42

Hybrid Inverse Reinforcement Learning

Juntao Ren, Gokul Swamy, Steven Wu et al.

inverse reinforcement learningimitation learninghybrid reinforcement learningexpert-competitive rl+4

29

ICLR 2024arXiv:2311.12996

#43

RLIF: Interactive Imitation Learning as Reinforcement Learning

Jianlan Luo, Perry Dong, Yuexiang Zhai et al.

NEURIPS 2025arXiv:2503.22230

#44

Exploring Data Scaling Trends and Effects in Reinforcement Learning from Human Feedback

Wei Shen, Guanlin Liu, Yu Yue et al.

ICLR 2024arXiv:2404.01220

#45

Entity-Centric Reinforcement Learning for Object Manipulation from Pixels

Dan Haramati, Tal Daniel, Aviv Tamar

ICML 2024arXiv:2402.04764

#46

Code as Reward: Empowering Reinforcement Learning with VLMs

David Venuto, Mohammad Sami Nur Islam, Martin Klissarov et al.

vision-language modelsreinforcement learningreward function generationcode generation+3

AAAI 2024arXiv:2210.09241

#47

Reinforcement Learning and Data

Generation for Syntax-Guided Synthesis

offline reinforcement learningdistributional shiftbehavior policy constraintsupport alignment+3

ICML 2024arXiv:2312.12275

#48

Emergence of In-Context Reinforcement Learning from Noise Distillation

Ilya Zisman, Vladislav Kurenkov, Alexander Nikulin et al.

in-context reinforcement learningnoise-induced curriculumdata acquisitionsynthetic noise injection+2

ICML 2024arXiv:2406.00645

#49

FuRL: Visual-Language Models as Fuzzy Rewards for Reinforcement Learning

Yuwei Fu, Haichao Zhang, di wu et al.

visual-language modelsreinforcement learningsparse reward tasksreward alignment+3

ICML 2024arXiv:2402.02868

#50

Fine-tuning Reinforcement Learning Models is Secretly a Forgetting Mitigation Problem

Maciej Wołczyk, Bartłomiej Cupiał, Mateusz Ostaszewski et al.

reinforcement learningfine-tuningforgetting mitigationknowledge retention+4

ECCV 2024arXiv:2409.18343

#51

Improving Agent Behaviors with RL Fine-tuning for Autonomous Driving

Zhenghao Peng, Wenjie Luo, Yiren Lu et al.

autonomous drivingagent behavior modelingreinforcement learning fine-tuningdistribution shift+4

25

CVPR 2024arXiv:2312.09337

#52

Promptable Behaviors: Personalizing Multi-Objective Rewards from Human Preferences

Minyoung Hwang, Luca Weihs, Chanwoo Park et al.

25

NEURIPS 2025arXiv:2505.20347

#53

SeRL: Self-play Reinforcement Learning for Large Language Models with Limited Data

Wenkai Fang, Shunyu Liu, Yang Zhou et al.

reinforcement learninglarge language modelsself-instruction generationself-rewarding mechanisms+4

25

ICML 2025arXiv:2505.07395

#54

ReinboT: Amplifying Robot Visual-Language Manipulation with Reinforcement Learning

Hongyin Zhang, Zifeng Zhuang, Han Zhao et al.

24

AAAI 2025arXiv:2412.11120

#55

Latent Reward: LLM-Empowered Credit Assignment in Episodic Reinforcement Learning

Yun Qu, Yuhang Jiang, Boyuan Wang et al.

credit assignmentepisodic reinforcement learningreward redistributionlatent reward+3

24

ICLR 2025arXiv:2412.12098

#56

MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization

Bhavya, Stelian Coros, Andreas Krause et al.

24

ICLR 2024arXiv:2310.11971

#57

Improving Generalization of Alignment with Human Preferences through Group Invariant Learning

Rui Zheng, Wei Shen, Yuan Hua et al.

23

ICLR 2024arXiv:2307.13372

#58

Submodular Reinforcement Learning

Manish Prajapat, Mojmir Mutny, Melanie Zeilinger et al.

ICLR 2024arXiv:2102.09407

#59

Adaptive Rational Activations to Boost Deep Reinforcement Learning

Quentin Delfosse, Patrick Schramowski, Martin Mundt et al.

ICLR 2024arXiv:2403.07548

#60

Online Continual Learning for Interactive Instruction Following Agents

Byeonghwi Kim, Minhyuk Seo, Jonghyun Choi

ICML 2024arXiv:2405.07162

#61

Learning Reward for Robot Skills Using Large Language Models via Self-Alignment

Yuwei Zeng, Yao Mu, Lin Shao

reward function learninglarge language modelsrobot skillsself-alignment process+3

ICML 2024arXiv:2306.02865

#62

Seizing Serendipity: Exploiting the Value of Past Success in Off-Policy Actor-Critic

Tianying Ji, Yu Luo, Fuchun Sun et al.

off-policy reinforcement learningq-value estimationactor-critic methodscontinuous control tasks+3

21

NEURIPS 2025arXiv:2505.16394

#63

Raw2Drive: Reinforcement Learning with Aligned World Models for End-to-End Autonomous Driving (in CARLA v2)

Zhenjie Yang, Xiaosong Jia, Qifeng Li et al.

reinforcement learningautonomous drivingworld modelsmodel-based reinforcement learning+4

21

ICLR 2025arXiv:2501.12735

#64

Online Preference Alignment for Language Models via Count-based Exploration

Chenjia Bai, Yang Zhang, Shuang Qiu et al.

reinforcement learning from human feedbackonline preference alignmentlarge language modelscount-based exploration+3

20

CVPR 2025arXiv:2503.11240

#65

Towards Better Alignment: Training Diffusion Models with Reinforcement Learning Against Sparse Rewards

Zijing Hu, Fengda Zhang, Long Chen et al.

20

NEURIPS 2025arXiv:2506.05316

#66

Improving Data Efficiency for LLM Reinforcement Fine-tuning Through Difficulty-targeted Online Data Selection and Rollout Replay

Yifan Sun, Jingyan Shen, Yibin Wang et al.

20

ICLR 2025arXiv:2411.00418

#67

SELF-EVOLVED REWARD LEARNING FOR LLMS

Chenghua Huang, Zhizhen Fan, Lu Wang et al.

reinforcement learning from human feedbackreward model trainingself-evolved learninglanguage model alignment+3

19

NEURIPS 2025arXiv:2505.13934

#68

RLVR-World: Training World Models with Reinforcement Learning

Jialong Wu, Shaofeng Yin, Ningya Feng et al.

19

ICML 2025arXiv:2410.14972

#69

MENTOR: Mixture-of-Experts Network with Task-Oriented Perturbation for Visual Reinforcement Learning

Suning Huang, Zheyu Zhang, Tianhai Liang et al.

ICML 2025arXiv:2502.01819

#70

Score as Action: Fine Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning

Hanyang Zhao, Haoxian Chen, Ji Zhang et al.

ICLR 2025arXiv:2410.04612

#71

Regressing the Relative Future: Efficient Policy Optimization for Multi-turn RLHF

Zhaolin Gao, Wenhao Zhan, Jonathan Chang et al.

reinforcement learning from human feedbackmulti-turn dialoguepolicy optimizationcovariate shift+4

ICLR 2025arXiv:2408.03029

#72

Highly Efficient Self-Adaptive Reward Shaping for Reinforcement Learning

Haozhe Ma, Zhengding Luo, Thanh Vinh Vo et al.

ICLR 2024arXiv:2310.01737

#73

Blending Imitation and Reinforcement Learning for Robust Policy Improvement

Xuefeng Liu, Takuma Yoneda, Rick Stevens et al.

AAAI 2024arXiv:2312.00198

#74

Optimal Attack and Defense for Reinforcement Learning

Jeremy McMahan, Young Wu, Xiaojin Zhu et al.

NEURIPS 2025arXiv:2506.20520

#75

Asymmetric REINFORCE for off-Policy Reinforcement Learning: Balancing positive and negative rewards

Charles Arnal, Gaëtan Narozniak, Vivien Cabannes et al.

reinforcement learningoff-policy methodspolicy improvement guaranteereward shaping+3

ICML 2024arXiv:2403.03811

#76

Incentivized Learning in Principal-Agent Bandit Games

Antoine Scheid, Daniil Tiapkin, Etienne Boursier et al.

principal-agent gamesbandit problemsincentive designmechanism design+3

ICML 2024arXiv:2404.18909

#77

Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty

Laixi Shi, Eric Mazumdar, Yuejie Chi et al.

multi-agent reinforcement learningdistributionally robust markov gamesrobust equilibrium strategiesgame-theoretic equilibria+4

ICML 2024arXiv:2403.06966

#78

Acquiring Diverse Skills using Curriculum Reinforcement Learning with Mixture of Experts

Onur Celik, Aleksandar Taranovic, Gerhard Neumann

curriculum reinforcement learningmixture of expertsdiverse skill learningcontextual motion primitives+4

ICLR 2024arXiv:2310.07932

#79

What Matters to You? Towards Visual Representation Alignment for Robot Learning

Thomas Tian, Chenfeng Xu, Masayoshi Tomizuka et al.

CVPR 2025arXiv:2408.15270

#80

SkillMimic: Learning Basketball Interaction Skills from Demonstrations

Yinhuai Wang, Qihan Zhao, Runyi Yu et al.

human-object interactionimitation learningbasketball skill learninginteraction skill transfer+3

AAAI 2024arXiv:2310.02456

#81

Learning Optimal Advantage from Preferences and Mistaking It for Reward

W Bradley Knox, Stephane Hatgis-Kessell, Sigurdur Orn Adalgeirsson et al.

reward function learninghuman preference modelingregret preference modelpartial return assumption+4

AAAI 2025arXiv:2502.18510

#82

Multi-Teacher Knowledge Distillation with Reinforcement Learning for Visual Recognition

Chuanguang Yang, XinQiang Yu, Han Yang et al.

ECCV 2024arXiv:2303.10571

#83

Reinforcement Learning Friendly Vision-Language Model for Minecraft

Haobin Jiang, Junpeng Yue, Hao Luo et al.

vision-language modelreinforcement learning friendlycontrastive learning frameworkintrinsic reward function+4

ICLR 2025arXiv:2410.09486

#84

ActSafe: Active Exploration with Safety Constraints for Reinforcement Learning

Yarden As, Bhavya, Lenart Treven et al.

reinforcement learningsafe explorationmodel-based rlprobabilistic dynamics model+3

ICLR 2025arXiv:2502.12130

#85

Scaling Autonomous Agents via Automatic Reward Modeling And Planning

Zhenfang Chen, Delin Chen, Rui Sun et al.

automatic reward modelingmulti-step decision-makingllm-based agentstask planning+3

ICML 2025arXiv:2502.04270

#86

PILAF: Optimal Human Preference Sampling for Reward Modeling

Yunzhen Feng, Ariel Kwiatkowski, Kunhao Zheng et al.

AAAI 2024arXiv:2312.11118

#87

Explaining Reinforcement Learning Agents through Counterfactual Action Outcomes

Yotam Amitai, Yael Friedler, Ofra Amir

AAAI 2024arXiv:2307.16348

#88

Rating-Based Reinforcement Learning

Devin White, Mingkang Wu, Ellen Novoseller et al.

reinforcement learninghuman ratingspreference-based learningrating prediction model+3

AAAI 2024arXiv:2312.09539

#89

Situation-Dependent Causal Influence-Based Cooperative Multi-Agent Reinforcement Learning

Xiao Du, Yutong Ye, Pengyu Zhang et al.

ECCV 2024arXiv:2407.15626

#90

Reinforcement Learning Meets Visual Odometry

Nico Messikommer, Giovanni Cioffi, Mathias Gehrig et al.

visual odometryreinforcement learningkeyframe selectionsequential decision-making+4

ICLR 2024arXiv:2305.18505

#91

Provable Reward-Agnostic Preference-Based Reinforcement Learning

Wenhao Zhan, Masatoshi Uehara, Wen Sun et al.

ICLR 2024arXiv:2310.05422

#92

Reward-Consistent Dynamics Models are Strongly Generalizable for Offline Reinforcement Learning

Fan-Ming Luo, Tian Xu, Xingchen Cao et al.

NEURIPS 2025arXiv:2506.08745

#93

Consistent Paths Lead to Truth: Self-Rewarding Reinforcement Learning for LLM Reasoning

Kongcheng Zhang, QI YAO, Shunyu Liu et al.

self-rewarding reinforcement learninglarge language model reasoningreasoning trajectory consistencyintrinsic reward mechanism+4

NEURIPS 2025arXiv:2505.15456

#94

Teaching Language Models to Evolve with Users: Dynamic Profile Modeling for Personalized Alignment

Weixiang Zhao, Xingyu Sui, Yulin Hu et al.

personalized alignmentuser profile modelingreinforcement learning frameworkdialogue systems+4

ICLR 2024arXiv:2310.07433

#95

Imitation Learning from Observation with Automatic Discount Scheduling

Yuyang Liu, Weijun Dong, Yingdong Hu et al.

NEURIPS 2025arXiv:2504.03206

#96

Enhancing Personalized Multi-Turn Dialogue with Curiosity Reward

Yanming Wan, Jiaxing Wu, Marwa Abdulhai et al.

personalized dialogue systemsmulti-turn reinforcement learningcuriosity reward mechanismuser modeling+4

AAAI 2025arXiv:2412.10713

#97

RAT: Adversarial Attacks on Deep Reinforcement Agents for Targeted Behaviors

Fengshuo Bai, Runze Liu, Yali Du et al.

adversarial attacksdeep reinforcement learningtargeted behavior attacksintention policy+4

12

ICLR 2024arXiv:2310.09144

#98

Goodhart's Law in Reinforcement Learning

Jacek Karwowski, Oliver Hayman, Xingjian Bai et al.

12

ICML 2024arXiv:2402.01361

#99

To the Max: Reinventing Reward in Reinforcement Learning

Grigorii Veviurko, Wendelin Boehmer, Mathijs de Weerdt

reinforcement learningreward function designmax-reward optimizationgoal-reaching environments+2

11

AAAI 2024arXiv:2308.02223

#100

ESRL: Efficient Sampling-Based Reinforcement Learning for Sequence Generation

Chenglong Wang, Hang Zhou, Yimin Hu et al.

11