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

233 papers, page 4 of 5

151. ICLR 2023Optimistic Exploration with Learned Features Provably Solves Markov Decision Processes with Neural Dynamics
152. ICLR 2023Order Matters: Agent-by-agent Policy Optimization
153. ICLR 2023Outcome-directed Reinforcement Learning by Uncertainty \& Temporal Distance-Aware Curriculum Goal Generation
154. ICLR 2023PAC Reinforcement Learning for Predictive State Representations
155. ICLR 2023Partially Observable RL with B-Stability: Unified Structural Condition and Sharp Sample-Efficient Algorithms
156. ICLR 2023PD-MORL: Preference-Driven Multi-Objective Reinforcement Learning Algorithm
157. ICLR 2023Performance Bounds for Model and Policy Transfer in Hidden-parameter MDPs
158. ICLR 2023Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes
159. ICLR 2023Pink Noise Is All You Need: Colored Noise Exploration in Deep Reinforcement Learning
160. ICLR 2023Planning Goals for Exploration
161. ICLR 2023Planning with Sequence Models through Iterative Energy Minimization
162. ICLR 2023Policy Expansion for Bridging Offline-to-Online Reinforcement Learning
163. ICLR 2023Policy-Based Self-Competition for Planning Problems
164. ICLR 2023POPGym: Benchmarking Partially Observable Reinforcement Learning
165. ICLR 2023Population-size-Aware Policy Optimization for Mean-Field Games
166. ICLR 2023Powderworld: A Platform for Understanding Generalization via Rich Task Distributions
167. ICLR 2023Preference Transformer: Modeling Human Preferences using Transformers for RL
168. ICLR 2023Priors, Hierarchy, and Information Asymmetry for Skill Transfer in Reinforcement Learning
169. ICLR 2023Proactive Multi-Camera Collaboration for 3D Human Pose Estimation
170. ICLR 2023Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks
171. ICLR 2023Provably Efficient Lifelong Reinforcement Learning with Linear Representation
172. ICLR 2023Provably Efficient Risk-Sensitive Reinforcement Learning: Iterated CVaR and Worst Path
173. ICLR 2023Q-Pensieve: Boosting Sample Efficiency of Multi-Objective RL Through Memory Sharing of Q-Snapshots
174. ICLR 2023Quality-Similar Diversity via Population Based Reinforcement Learning
175. ICLR 2023Quasi-optimal Reinforcement Learning with Continuous Actions
176. ICLR 2023ReAct: Synergizing Reasoning and Acting in Language Models
177. ICLR 2023Recursive Time Series Data Augmentation
178. ICLR 2023Relative Behavioral Attributes: Filling the Gap between Symbolic Goal Specification and Reward Learning from Human Preferences
179. ICLR 2023Replay Memory as An Empirical MDP: Combining Conservative Estimation with Experience Replay
180. ICLR 2023Represent to Control Partially Observed Systems: Representation Learning with Provable Sample Efficiency
181. ICLR 2023Representation Learning for Low-rank General-sum Markov Games
182. ICLR 2023ResAct: Reinforcing Long-term Engagement in Sequential Recommendation with Residual Actor
183. ICLR 2023Revisiting Intrinsic Reward for Exploration in Procedurally Generated Environments
184. ICLR 2023Revocable Deep Reinforcement Learning with Affinity Regularization for Outlier-Robust Graph Matching
185. ICLR 2023Reward Design with Language Models
186. ICLR 2023Risk-Aware Reinforcement Learning with Coherent Risk Measures and Non-linear Function Approximation
187. ICLR 2023RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch
188. ICLR 2023ROCO: A General Framework for Evaluating Robustness of Combinatorial Optimization Solvers on Graphs
189. ICLR 2023RPM: Generalizable Multi-Agent Policies for Multi-Agent Reinforcement Learning
190. ICLR 2023Safe Exploration Incurs Nearly No Additional Sample Complexity for Reward-Free RL
191. ICLR 2023Safe Reinforcement Learning From Pixels Using a Stochastic Latent Representation
192. ICLR 2023Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks
193. ICLR 2023Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier
194. ICLR 2023Scalable Batch-Mode Deep Bayesian Active Learning via Equivalence Class Annealing
195. ICLR 2023Scaling Laws for a Multi-Agent Reinforcement Learning Model
196. ICLR 2023Scaling Pareto-Efficient Decision Making via Offline Multi-Objective RL
197. ICLR 2023Simple Emergent Action Representations from Multi-Task Policy Training
198. ICLR 2023Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective
199. ICLR 2023SMART: Self-supervised Multi-task pretrAining with contRol Transformers
200. ICLR 2023Solving Continuous Control via Q-learning

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.