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 5 of 24

201. ICLR 2024Learning Multi-Agent Communication from Graph Modeling Perspective
202. ICLR 2024Learning Multi-Agent Communication with Contrastive Learning
203. ICLR 2024Learning Nash Equilibria in Rank-1 Games
204. ICLR 2024Learning to Act from Actionless Videos through Dense Correspondences
205. ICLR 2024Learning to Act without Actions
206. ICLR 2024Learning to Make Adherence-aware Advice
207. ICLR 2024Leftover Lunch: Advantage-based Offline Reinforcement Learning for Language Models
208. ICLR 2024Less or More From Teacher: Exploiting Trilateral Geometry For Knowledge Distillation
209. ICLR 2024Local Search GFlowNets
210. ICLR 2024Locality Sensitive Sparse Encoding for Learning World Models Online
211. ICLR 2024LOQA: Learning with Opponent Q-Learning Awareness
212. ICLR 2024Making RL with Preference-based Feedback Efficient via Randomization
213. ICLR 2024MAMBA: an Effective World Model Approach for Meta-Reinforcement Learning
214. ICLR 2024Massively Scalable Inverse Reinforcement Learning in Google Maps
215. ICLR 2024Mastering Memory Tasks with World Models
216. ICLR 2024Maximum Entropy Heterogeneous-Agent Reinforcement Learning
217. ICLR 2024Maximum Entropy Model Correction in Reinforcement Learning
218. ICLR 2024Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy
219. ICLR 2024Meta Inverse Constrained Reinforcement Learning: Convergence Guarantee and Generalization Analysis
220. ICLR 2024Meta-Evolve: Continuous Robot Evolution for One-to-many Policy Transfer
221. ICLR 2024METRA: Scalable Unsupervised RL with Metric-Aware Abstraction
222. ICLR 2024MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback
223. ICLR 2024Motif: Intrinsic Motivation from Artificial Intelligence Feedback
224. ICLR 2024Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts
225. ICLR 2024Multimodal Web Navigation with Instruction-Finetuned Foundation Models
226. ICLR 2024Negatively Correlated Ensemble Reinforcement Learning for Online Diverse Game Level Generation
227. ICLR 2024ODICE: Revealing the Mystery of Distribution Correction Estimation via Orthogonal-gradient Update
228. ICLR 2024Off-Policy Primal-Dual Safe Reinforcement Learning
229. ICLR 2024Offline Data Enhanced On-Policy Policy Gradient with Provable Guarantees
230. ICLR 2024Offline RL with Observation Histories: Analyzing and Improving Sample Complexity
231. ICLR 2024OMNI: Open-endedness via Models of human Notions of Interestingness
232. ICLR 2024On Double Descent in Reinforcement Learning with LSTD and Random Features
233. ICLR 2024On Representation Complexity of Model-based and Model-free Reinforcement Learning
234. ICLR 2024On Stationary Point Convergence of PPO-Clip
235. ICLR 2024On the Expressivity of Objective-Specification Formalisms in Reinforcement Learning
236. ICLR 2024On the Hardness of Constrained Cooperative Multi-Agent Reinforcement Learning
237. ICLR 2024On the Joint Interaction of Models, Data, and Features
238. ICLR 2024On the Role of General Function Approximation in Offline Reinforcement Learning
239. ICLR 2024On Trajectory Augmentations for Off-Policy Evaluation
240. ICLR 2024On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes
241. ICLR 2024Open the Black Box: Step-based Policy Updates for Temporally-Correlated Episodic Reinforcement Learning
242. ICLR 2024OpenChat: Advancing Open-source Language Models with Mixed-Quality Data
243. ICLR 2024Optimal Sample Complexity for Average Reward Markov Decision Processes
244. ICLR 2024PAE: Reinforcement Learning from External Knowledge for Efficient Exploration
245. ICLR 2024PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback
246. ICLR 2024Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning
247. ICLR 2024Physics-Regulated Deep Reinforcement Learning: Invariant Embeddings
248. ICLR 2024Piecewise Linear Parametrization of Policies: Towards Interpretable Deep Reinforcement Learning
249. ICLR 2024PILOT: An $\mathcal{O}(1/K)$-Convergent Approach for Policy Evaluation with Nonlinear Function Approximation
250. ICLR 2024Plan-Seq-Learn: Language Model Guided RL for Solving Long Horizon Robotics Tasks

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.