Reinforcement Learning papers, 2023–2026

Key findings

• Reinforcement Learning went from 1,070 papers in 2023 to 2,985 in 2026, roughly 2.8x in three years.
• NeurIPS publishes the most Reinforcement Learning work: 2,494 papers from 2023 to 2026, 36% of the four-venue total.
• The fastest-growing overlap is with Reasoning Models: papers tagged with both rose from 9 in 2023 to 437 in 2026.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026\texttt{FEROM}: Frontier Endogenous Reveal-Order Marginal Policy Optimization for Masked Diffusion LMs
• ICML 2026$\text{DT}^\text{2}$: Decision-Targeted Digital Twins
• ICLR 2026$\nabla$-Reasoner: LLM Reasoning via Test-Time Gradient Descent in Textual Space
• CVPR 2026A Causal Marriage between VLM and IRM from Understanding to
• NeurIPS 2025$\texttt{G1}$: Teaching LLMs to Reason on Graphs with Reinforcement Learning
• ICML 2025A Computationally Efficient Algorithm for Infinite-Horizon Average-Reward Linear MDPs
• ICLR 2025$\phi$-Update: A Class of Policy Update Methods with Policy Convergence Guarantee
• CVPR 2025All-Optical Nonlinear Diffractive Deep Network for Ultrafast Image Denoising
• NeurIPS 2024A Critical Evaluation of AI Feedback for Aligning Large Language Models
• ICML 2024${\rm E}(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning
• ICLR 2024A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning
• CVPR 2024DMR: Decomposed Multi-Modality Representations for Frames and Events Fusion in Visual Reinforcement Learning
• NeurIPS 2023“Why Not Looking backward?” A Robust Two-Step Method to Automatically Terminate Bayesian Optimization
• ICML 2023A Connection between One-Step RL and Critic Regularization in Reinforcement Learning
• ICLR 2023$O(T^{-1})$ Convergence of Optimistic-Follow-the-Regularized-Leader in Two-Player Zero-Sum Markov Games
• CVPR 2023"Seeing" Electric Network Frequency From Events
• NeurIPS 2026$\varphi$TD: Distributional Reinforcement Learning using Characteristic Functions
• ICML 2026$\textit{S}$-SPPO: Semantic-Calibrated Self-Play Preference Optimization
• ICLR 2026$AutoDrive\text{-}P^3$: Unified Chain of Perception–Prediction–Planning Thought via Reinforcement Fine-Tuning
• CVPR 2026AdaptVision Efficient Vision-Language Models via Adaptive Visual Acquisition

All Reinforcement Learning papers

1,190 papers, page 24 of 24

1151. NeurIPS 2024The Sample-Communication Complexity Trade-off in Federated Q-Learning
1152. NeurIPS 2024The surprising efficiency of temporal difference learning for rare event prediction
1153. NeurIPS 2024The Surprising Ineffectiveness of Pre-Trained Visual Representations for Model-Based Reinforcement Learning
1154. NeurIPS 2024The Value of Reward Lookahead in Reinforcement Learning
1155. NeurIPS 2024Time-Constrained Robust MDPs
1156. NeurIPS 2024Towards an Information Theoretic Framework of Context-Based Offline Meta-Reinforcement Learning
1157. NeurIPS 2024Towards Effective Planning Strategies for Dynamic Opinion Networks
1158. NeurIPS 2024Towards Next-Generation Logic Synthesis: A Scalable Neural Circuit Generation Framework
1159. NeurIPS 2024Towards the Transferability of Rewards Recovered via Regularized Inverse Reinforcement Learning
1160. NeurIPS 2024Towards Visual Text Design Transfer Across Languages
1161. NeurIPS 2024Trajectory Data Suffices for Statistically Efficient Learning in Offline RL with Linear $q^\pi$-Realizability and Concentrability
1162. NeurIPS 2024Transformers as Game Players: Provable In-context Game-playing Capabilities of Pre-trained Models
1163. NeurIPS 2024Transition Constrained Bayesian Optimization via Markov Decision Processes
1164. NeurIPS 2024Truncated Variance Reduced Value Iteration
1165. NeurIPS 2024TurboHopp: Accelerated Molecule Scaffold Hopping with Consistency Models
1166. NeurIPS 2024Two-way Deconfounder for Off-policy Evaluation in Causal Reinforcement Learning
1167. NeurIPS 2024UltraMedical: Building Specialized Generalists in Biomedicine
1168. NeurIPS 2024Uncertainty-based Offline Variational Bayesian Reinforcement Learning for Robustness under Diverse Data Corruptions
1169. NeurIPS 2024Understanding and Improving Training-free Loss-based Diffusion Guidance
1170. NeurIPS 2024Understanding Model Selection for Learning in Strategic Environments
1171. NeurIPS 2024Uniform Last-Iterate Guarantee for Bandits and Reinforcement Learning
1172. NeurIPS 2024Unlock the Intermittent Control Ability of Model Free Reinforcement Learning
1173. NeurIPS 2024Using Unity to Help Solve Reinforcement Learning
1174. NeurIPS 2024Value-Based Deep Multi-Agent Reinforcement Learning with Dynamic Sparse Training
1175. NeurIPS 2024Variational Delayed Policy Optimization
1176. NeurIPS 2024Verifiably Robust Conformal Prediction
1177. NeurIPS 2024Verified Safe Reinforcement Learning for Neural Network Dynamic Models
1178. NeurIPS 2024Vision-Language Navigation with Energy-Based Policy
1179. NeurIPS 2024Warm-up Free Policy Optimization: Improved Regret in Linear Markov Decision Processes
1180. NeurIPS 2024WFCRL: A Multi-Agent Reinforcement Learning Benchmark for Wind Farm Control
1181. NeurIPS 2024When LLM Meets DRL: Advancing Jailbreaking Efficiency via DRL-guided Search
1182. NeurIPS 2024When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL
1183. NeurIPS 2024When Your AIs Deceive You: Challenges of Partial Observability in Reinforcement Learning from Human Feedback
1184. NeurIPS 2024WizardArena: Post-training Large Language Models via Simulated Offline Chatbot Arena
1185. NeurIPS 2024WorldCoder, a Model-Based LLM Agent: Building World Models by Writing Code and Interacting with the Environment
1186. NeurIPS 2024Worst-Case Offline Reinforcement Learning with Arbitrary Data Support
1187. NeurIPS 2024Would I Lie To You? Inference Time Alignment of Language Models using Direct Preference Heads
1188. NeurIPS 2024XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX
1189. NeurIPS 2024Zero-Shot Reinforcement Learning from Low Quality Data
1190. NeurIPS 2024ZSC-Eval: An Evaluation Toolkit and Benchmark for Multi-agent Zero-shot Coordination

FAQ

How many Reinforcement Learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

6,885 in total: 1,070 in 2023, 1,190 in 2024, 1,640 in 2025, 2,985 in 2026.

How many Reinforcement Learning papers are at NeurIPS 2026?

NeurIPS 2026 has 760 Reinforcement Learning papers, versus 784 the year before.

How many Reinforcement Learning papers are at ICLR 2026?

ICLR 2026 has 911 Reinforcement Learning papers, versus 379 the year before.

How many Reinforcement Learning papers are at ICML 2026?

ICML 2026 has 1,021 Reinforcement Learning papers, versus 405 the year before.

How many Reinforcement Learning papers are at CVPR 2026?

CVPR 2026 has 293 Reinforcement Learning papers, versus 72 the year before.

Which conference publishes the most Reinforcement Learning papers?

NeurIPS, with 2,494 papers from 2023 to 2026.