Model-Based RL

ICLR 2024arXiv:2310.16828

#2

TD-MPC2: Scalable, Robust World Models for Continuous Control

Nicklas Hansen, Hao Su, Xiaolong Wang

293

ICLR 2024arXiv:2310.12921

#3

OccWorld: Learning a 3D Occupancy World Model for Autonomous Driving

Wenzhao Zheng, Weiliang Chen, Yuanhui Huang et al.

ToolRL: Reward is All Tool Learning Needs

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

Vision-Language Models are Zero-Shot Reward Models for Reinforcement Learning

Juan Rocamonde, Victoriano Montesinos, Elvis Nava et al.

133

CVPR 2024arXiv:2312.02010

#6

Towards Learning a Generalist Model for Embodied Navigation

Duo Zheng, Shijia Huang, Lin Zhao et al.

117

ICLR 2025arXiv:2411.02337

#7

WebRL: Training LLM Web Agents via Self-Evolving Online Curriculum Reinforcement Learning

Zehan Qi, Xiao Liu, Iat Long Iong et al.

llm web agentsonline curriculum reinforcement learningself-evolving curriculumoutcome-supervised reward model+3

110

CVPR 2024arXiv:2304.00962

#8

RegionPLC: Regional Point-Language Contrastive Learning for Open-World 3D Scene Understanding

Jihan Yang, Runyu Ding, Weipeng DENG et al.

103

NeurIPS 2025arXiv:2505.24864

#9

ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Mingjie Liu, Shizhe Diao, Ximing Lu et al.

reinforcement learningreasoning capabilitieskl divergence controlreference policy resetting+4

96

ICLR 2024arXiv:2311.01017

#10

Copilot4D: Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion

Lunjun Zhang, Yuwen Xiong, Ze Yang et al.

92

ICLR 2024arXiv:2310.04373

#11

Confronting Reward Model Overoptimization with Constrained RLHF

Ted Moskovitz, Aaditya Singh, DJ Strouse et al.

73

ICLR 2024arXiv:2310.08887

#12

METRA: Scalable Unsupervised RL with Metric-Aware Abstraction

Seohong Park, Oleh Rybkin, Sergey Levine

68

NeurIPS 2025arXiv:2504.07954

#13

HAMSTER: Hierarchical Action Models for Open-World Robot Manipulation

Yi Li, Yuquan Deng, Jesse Zhang et al.

Perception-R1: Pioneering Perception Policy with Reinforcement Learning

En Yu, Kangheng Lin, Liang Zhao et al.

58

ICCV 2025arXiv:2412.18607

#15

DrivingGPT: Unifying Driving World Modeling and Planning with Multi-modal Autoregressive Transformers

Yuntao Chen, Yuqi Wang, Zhaoxiang Zhang

44

reinforcement learningautonomous drivingworld modellatent state space+4

#16

Think2Drive: Efficient Reinforcement Learning by Thinking with Latent World Model for Autonomous Driving (in CARLA-v2)

Qifeng Li, Xiaosong Jia, Shaobo Wang et al.

ECCV 2024

43

ICLR 2024arXiv:2302.08560

#17

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

Harshit Sikchi, Qinqing Zheng, Amy Zhang et al.

39

ICLR 2024arXiv:2307.07176

#18

SafeDreamer: Safe Reinforcement Learning with World Models

Weidong Huang, Jiaming Ji, Chunhe Xia et al.

34

ICLR 2025arXiv:2406.08407

#19

MMWorld: Towards Multi-discipline Multi-faceted World Model Evaluation in Videos

Xuehai He, Weixi Feng, Kaizhi Zheng et al.

multimodal video understandingworld model evaluationmultimodal language modelscounterfactual reasoning+3

34

NeurIPS 2025arXiv:2502.20694

#20

WorldModelBench: Judging Video Generation Models As World Models

Dacheng Li, Yunhao Fang, Yukang Chen et al.

video generation modelsworld modeling capabilitiesphysics adherenceinstruction-following evaluation+4

31

ECCV 2024arXiv:2409.18343

#21

Long-Context State-Space Video World Models

Ryan Po, Yotam Nitzan, Richard Zhang et al.

Dream to Manipulate: Compositional World Models Empowering Robot Imitation Learning with Imagination

Leonardo Barcellona, Andrii Zadaianchuk, Davide Allegro et al.

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

23

ICLR 2025arXiv:2410.07927

#24

Pre-Training Goal-based Models for Sample-Efficient Reinforcement Learning

Haoqi Yuan, Zhancun Mu, Feiyang Xie et al.

Efficient Reinforcement Learning with Large Language Model Priors

Xue Yan, Yan Song, Xidong Feng et al.

20

ICLR 2025arXiv:2405.18418

#26

Hierarchical World Models as Visual Whole-Body Humanoid Controllers

Nick Hansen, Jyothir S V, Vlad Sobal et al.

whole-body controlhumanoid roboticsvisual observationshierarchical world model+4

19

ICLR 2024arXiv:2401.13034

#27

Locality Sensitive Sparse Encoding for Learning World Models Online

Zichen Liu, Chao Du, Wee Sun Lee et al.

18

NeurIPS 2025arXiv:2505.05495

#28

MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization

Bhavya, Stelian Coros, Andreas Krause et al.

Learning 3D Persistent Embodied World Models

Siyuan Zhou, Yilun Du, Yuncong Yang et al.

17

ICLR 2024arXiv:2310.07220

#30

COPlanner: Plan to Roll Out Conservatively but to Explore Optimistically for Model-Based RL

Xiyao Wang, Ruijie Zheng, Yanchao Sun et al.

17

ICLR 2024arXiv:2403.10760

#31

CORN: Contact-based Object Representation for Nonprehensile Manipulation of General Unseen Objects

Yoonyoung Cho, Junhyek Han, Yoontae Cho et al.

16

AAAI 2024arXiv:2310.02456

#32

Reinforcement Learning Finetunes Small Subnetworks in Large Language Models

Sagnik Mukherjee, Lifan Yuan, Dilek Hakkani-Tur et al.

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

15

ICLR 2025arXiv:2310.20025

#34

GOPlan: Goal-conditioned Offline Reinforcement Learning by Planning with Learned Models

Mianchu Wang, Rui Yang, Xi Chen et al.

15

ECCV 2024arXiv:2303.10571

#35

Reinforcement Learning Friendly Vision-Language Model for Minecraft

Haobin Jiang, Junpeng Yue, Hao Luo et al.

14

CVPR 2024arXiv:2312.09056

#36

ReCoRe: Regularized Contrastive Representation Learning of World Model

Rudra P, K. Poudel, Harit Pandya et al.

14

ICLR 2024arXiv:2307.12062

#37

Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations

Yongyuan Liang, Yanchao Sun, Ruijie Zheng et al.

12

ICLR 2025arXiv:2501.13072

#38

AdaWM: Adaptive World Model based Planning for Autonomous Driving

Hang Wang, Xin Ye, Feng Tao et al.

world model reinforcement learningautonomous driving planningdistribution shiftdynamics model mismatch+4

12

ICLR 2025arXiv:2503.04416

#39

Learning Transformer-based World Models with Contrastive Predictive Coding

Maxime Burchi, Radu Timofte

transformer-based world modelscontrastive predictive codingmodel-based reinforcement learningnext state prediction+2

12

ICLR 2024arXiv:2306.03346

#40

Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data

Chongyi Zheng, Benjamin Eysenbach, Homer Walke et al.

11

ICLR 2024arXiv:2307.06175

#41

Learning Decentralized Partially Observable Mean Field Control for Artificial Collective Behavior

Kai Cui, Sascha Hauck, Christian Fabian et al.

10

ICLR 2025arXiv:2408.08994

#42

Model-based RL as a Minimalist Approach to Horizon-Free and Second-Order Bounds

Zhiyong Wang, Dongruo Zhou, John C.S. Lui et al.

10

NeurIPS 2025arXiv:2506.00070

#43

Open-World Reinforcement Learning over Long Short-Term Imagination

Jiajian Li, Qi Wang, Yunbo Wang et al.

Robot-R1: Reinforcement Learning for Enhanced Embodied Reasoning in Robotics

Dongyoung Kim, Huiwon Jang, Sumin Park et al.

reinforcement learningembodied reasoningrobot controlvision-language models+4

9

NeurIPS 2025arXiv:2505.11792

#45

Solver-Informed RL: Grounding Large Language Models for Authentic Optimization Modeling

Yitian Chen, Jingfan Xia, Siyu Shao et al.

optimization modelinglarge language modelsreinforcement learningsolver verification+4

9

AAAI 2024arXiv:2401.12497

#46

Building Minimal and Reusable Causal State Abstractions for Reinforcement Learning

Zizhao Wang, Caroline Wang, Xuesu Xiao et al.

causal state abstractionsreinforcement learningimplicit dynamics modelsfactored state spaces+4

9

NeurIPS 2025arXiv:2505.21996

#47

Rapidly Adapting Policies to the Real-World via Simulation-Guided Fine-Tuning

Patrick Yin, Tyler Westenbroek, Ching-An Cheng et al.

VAGEN: Reinforcing World Model Reasoning for Multi-Turn VLM Agents

Kangrui Wang, Pingyue Zhang, Zihan Wang et al.

Learning World Models for Interactive Video Generation

Taiye Chen, Xun Hu, Zihan Ding et al.

NeurIPS 2025arXiv:2506.12811

#50

Flow-Based Policy for Online Reinforcement Learning

Lei Lv, Yunfei Li, Yu Luo et al.

ICLR 2024arXiv:2311.01450

#51

DreamSmooth: Improving Model-based Reinforcement Learning via Reward Smoothing

Vint Lee, Pieter Abbeel, Youngwoon Lee

ICLR 2024arXiv:2306.03857

#52

Learning with a Mole: Transferable latent spatial representations for navigation without reconstruction

Guillaume Bono, Leonid Antsfeld, Assem Sadek et al.

ICLR 2024arXiv:2303.03284

#53

The Wasserstein Believer: Learning Belief Updates for Partially Observable Environments through Reliable Latent Space Models

Raphael Avalos, Florent Delgrange, Ann Nowe et al.

ICLR 2024arXiv:2503.16799

#54

Causally Aligned Curriculum Learning

Mingxuan Li, Junzhe Zhang, Elias Bareinboim

ICML 2025arXiv:2506.12822

#55

Enhancing Rating-Based Reinforcement Learning to Effectively Leverage Feedback from Large Vision-Language Models

Minh-Tung Luu, Younghwan Lee, Donghoon Lee et al.

ICLR 2025arXiv:2410.00564

#56

Scaling Offline Model-Based RL via Jointly-Optimized World-Action Model Pretraining

Jie Cheng, Ruixi Qiao, ma yingwei et al.

offline reinforcement learningmodel-based rlworld modeljoint optimization+4

NeurIPS 2025arXiv:2505.23150

#57

Empowering LLM Agents with Zero-Shot Optimal Decision-Making through Q-learning

Jiajun Chai, Sicheng Li, Yuqian Fu et al.

Distilling Reinforcement Learning Algorithms for In-Context Model-Based Planning

Jaehyeon Son, Soochan Lee, Gunhee Kim

Bigger, Regularized, Categorical: High-Capacity Value Functions are Efficient Multi-Task Learners

Michal Nauman, Marek Cygan, Carmelo Sferrazza et al.

6

AAAI 2025arXiv:2412.11253

#60

Are Expressive Models Truly Necessary for Offline RL?

Guan Wang, Haoyi Niu, Jianxiong Li et al.

6

ICML 2025arXiv:2411.00171

#61

EARL-BO: Reinforcement Learning for Multi-Step Lookahead, High-Dimensional Bayesian Optimization

Mujin Cheon, Jay Lee, Dong-Yeun Koh et al.

6

AAAI 2025arXiv:2412.17288

#62

UTILITY: Utilizing Explainable Reinforcement Learning to Improve Reinforcement Learning

Shicheng Liu, Minghui Zhu

Multi-Modal Grounded Planning and Efficient Replanning for Learning Embodied Agents with a Few Examples

Taewoong Kim, Byeonghwi Kim, Jonghyun Choi

5

ICLR 2025arXiv:2407.00699

#64

Scaling Offline RL via Efficient and Expressive Shortcut Models

Nicolas Espinosa-Dice, Yiyi Zhang, Yiding Chen et al.

Model-based Offline Reinforcement Learning with Lower Expectile Q-Learning

Kwanyoung Park, Youngwoon Lee

5

ICLR 2025arXiv:2506.02612

#66

Language Agents Meet Causality -- Bridging LLMs and Causal World Models

John Gkountouras, Matthias Lindemann, Phillip Lippe et al.

Simple, Good, Fast: Self-Supervised World Models Free of Baggage

Jan Robine, Marc Höftmann, Stefan Harmeling

CVPR 2025arXiv:2504.07095

#68

Scaling Few-Shot Learning for the Open World

Zhipeng Lin, Wenjing Yang, Haotian Wang et al.

Neural Motion Simulator Pushing the Limit of World Models in Reinforcement Learning

Chenjie Hao, Weyl Lu, Yifan Xu et al.

ICCV 2025arXiv:2503.08751

#70

Disentangled World Models: Learning to Transfer Semantic Knowledge from Distracting Videos for Reinforcement Learning

Qi Wang, Zhipeng Zhang, Baao Xie et al.

ICML 2025arXiv:2503.01584

#71

SENSEI: Semantic Exploration Guided by Foundation Models to Learn Versatile World Models

Cansu Sancaktar, Christian Gumbsch, Andrii Zadaianchuk et al.

ICML 2025arXiv:2407.08250

#72

Gradient Boosting Reinforcement Learning

Benjamin Fuhrer, Chen Tessler, Gal Dalal

ICML 2025arXiv:2410.14081

#73

Reward-free World Models for Online Imitation Learning

Shangzhe Li, Zhiao Huang, Hao Su

NeurIPS 2025arXiv:2412.05718

#74

RLZero: Direct Policy Inference from Language Without In-Domain Supervision

Harshit Sushil Sikchi, Siddhant Agarwal, Pranaya Jajoo et al.

language-conditioned reinforcement learningzero-shot policy inferenceunsupervised rl pretrainingvideo generative models+3

NeurIPS 2025arXiv:2506.06981

#75

Deep RL Needs Deep Behavior Analysis: Exploring Implicit Planning by Model-Free Agents in Open-Ended Environments

Riley Simmons-Edler, Ryan Badman, Felix Berg et al.

AAAI 2025arXiv:2503.01178

#76

Learning to Steer Markovian Agents under Model Uncertainty

Jiawei Huang, Vinzenz Thoma, Zebang Shen et al.

Differentiable Information Enhanced Model-Based Reinforcement Learning

Xiaoyuan Zhang, Xinyan Cai, Bo Liu et al.

ICLR 2025arXiv:2302.02182

#78

Online Reinforcement Learning in Non-Stationary Context-Driven Environments

Pouya Hamadanian, Arash Nasr-Esfahany, Malte Schwarzkopf et al.

ICLR 2025arXiv:2406.18450

#79

Preference Elicitation for Offline Reinforcement Learning

Alizée Pace, Bernhard Schölkopf, Gunnar Ratsch et al.

NeurIPS 2025arXiv:2506.06964

#80

Provably Efficient Online RLHF with One-Pass Reward Modeling

Long-Fei Li, Yu-Yang Qian, Peng Zhao et al.

Offline RL by Reward-Weighted Fine-Tuning for Conversation Optimization

Subhojyoti Mukherjee, Viet Lai, Raghavendra Addanki et al.

offline reinforcement learningreward-weighted fine-tuninglarge language modelsconversation optimization+2

NeurIPS 2025arXiv:2509.13341

#82

Imagined Autocurricula

Ahmet Hamdi Güzel, Matthew T Jackson, Jarek Liesen et al.

world modelsunsupervised environment designembodied environmentsprocedurally generated environments+3

NeurIPS 2025arXiv:2505.19281

#83

Mixture-of-Experts Meets In-Context Reinforcement Learning

Wenhao Wu, Fuhong Liu, Haoru Li et al.

A Snapshot of Influence: A Local Data Attribution Framework for Online Reinforcement Learning

Yuzheng Hu, Fan Wu, Haotian Ye et al.

data attributiononline reinforcement learningproximal policy optimizationgradient similarity+4

NeurIPS 2025arXiv:2502.02869

#85

Towards Large-Scale In-Context Reinforcement Learning by Meta-Training in Randomized Worlds

Fan Wang, Pengtao Shao, Yiming Zhang et al.

in-context reinforcement learningprocedurally generated mdpsmeta-trainingpolicy distillation+4

ICLR 2024arXiv:2403.04050

#86

Belief-Enriched Pessimistic Q-Learning against Adversarial State Perturbations

Xiaolin Sun, Zizhan Zheng

ICML 2025arXiv:2505.12204

#87

Of Mice and Machines: A Comparison of Learning Between Real World Mice and RL Agents

Shuo Han, German Espinosa, Junda Huang et al.

ICML 2025arXiv:2505.19923

#88

Learning to Trust Bellman Updates: Selective State-Adaptive Regularization for Offline RL

Qin-Wen Luo, Ming-Kun Xie, Ye-Wen Wang et al.

ICLR 2024arXiv:2403.14860

#89

Robust Model Based Reinforcement Learning Using $\mathcal{L}_1$ Adaptive Control

Minjun Sung, Sambhu Harimanas Karumanchi, Aditya Gahlawat et al.

ICML 2025arXiv:2505.05262

#90

Enhancing Cooperative Multi-Agent Reinforcement Learning with State Modelling and Adversarial Exploration

Andreas Kontogiannis, Konstantinos Papathanasiou, Yi Shen et al.

ICML 2025arXiv:2412.06877

#91

The Synergy of LLMs & RL Unlocks Offline Learning of Generalizable Language-Conditioned Policies with Low-fidelity Data

Thomas Pouplin, Katarzyna Kobalczyk, Hao Sun et al.

open-ended world simulationphysical social dynamicslanguage-driven procedural generationmulti-modal agent interface+4

#92

SimWorld: An Open-ended Simulator for Agents in Physical and Social Worlds

Xiaokang Ye, Jiawei Ren, Yan Zhuang et al.

NeurIPS 2025

ICLR 2025arXiv:2407.20651

#93

Towards Robust Zero-Shot Reinforcement Learning

Kexin ZHENG, Lauriane Teyssier, Yinan Zheng et al.

Towards Generalizable Reinforcement Learning via Causality-Guided Self-Adaptive Representations

Yupei Yang, Biwei Huang, Fan Feng et al.

reinforcement learning generalizationcausal representation learningenvironment space adaptationdistribution shift adaptation+4