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

2,079 papers, page 4 of 42

151. ICML 2026CompleteP for RL: Maintaining Feature Learning When Scaling Deep Reinforcement Learning
152. ICML 2026Compositional Behavioral Semantics for State Abstraction in Reinforcement Learning
153. ICML 2026Compositional Transduction with Latent Analogies for Offline Goal-Conditioned Reinforcement Learning
154. ICML 2026Compute Where it Counts: Self Optimizing Language Models
155. ICML 2026Conditional Equivalence of DPO and RLHF: Assumptions, Failure Modes, and Provable Alignment
156. ICML 2026Conformal Policy Control
157. ICML 2026ConPress: Learning Efficient Reasoning from Multi-Question Contextual Pressure
158. ICML 2026Consistent Zero-Shot Imitation with Contrastive Goal Inference
159. ICML 2026Constrained Flow Optimization via Sequential Fine-Tuning for Molecular Design
160. ICML 2026Constrained Meta Reinforcement Learning with Provable Test-Time Safety
161. ICML 2026Constrained Multi-Objective Reinforcement Learning with Max-Min Criterion
162. ICML 2026Context-Aware Reasoner: Enhancing Contextual Reasoning in Multimodal Large Language Models
163. ICML 2026Contextual Rollout Bandits for Reinforcement Learning with Verifiable Rewards
164. ICML 2026Contextualized Privacy Defense for LLM Agents
165. ICML 2026Contextualized Visual Personalization in Vision-Language Models
166. ICML 2026Continuity-Regularized Flow Matching for Offline Reinforcement Learning
167. ICML 2026Contrastive Reasoning Alignment: Reinforcement Learning from Hidden Representations
168. ICML 2026Controllable and Explainable Personality Sliders for LLMs at Inference Time
169. ICML 2026Convergence of Steepest Descent and Adam under Non-Uniform Smoothness
170. ICML 2026Convergence of Two-Timescale Markovian Stochastic Approximations with Applications in Reinforcement Learning
171. ICML 2026Conversation for Non-verifiable Learning: Self-Evolving Large Language Models through Meta-Evaluation
172. ICML 2026Convex Optimization for Alignment and Preference Learning on a Single GPU
173. ICML 2026CooT: Learning to Coordinate In-Context with Coordination Transformers
174. ICML 2026CoRe: Collaborative Reasoning via Cross Teaching
175. ICML 2026CoRe: Combined Rewards with Vision-Language Model Feedback for Preference-Aligned Reinforcement Learning
176. ICML 2026CorrectionPlanner: Self-Correction Planner with Reinforcement Learning in Autonomous Driving
177. ICML 2026Corruption-Tolerant Asynchronous Q-Learning with Near-Optimal Rates
178. ICML 2026Counterfactual Bootstrap for Robust Meta-Reinforcement Learning
179. ICML 2026Coupled Variational Reinforcement Learning for Language Model General Reasoning
180. ICML 2026Covariance Volume Maximization for Embodied Latent Exploration in Deep Reinforcement Learning
181. ICML 2026CPMöbius: Iterative Coach–Player Reasoning for Data-Free Reinforcement Learning
182. ICML 2026Credit-assigned Policy Gradient for Early Stage Retrieval in Two-stage Ranking
183. ICML 2026CRPO: Character-centric Group Relative Policy Optimization for Role-aware Reasoning in Role-playing Agents
184. ICML 2026CSG: Cognitive Structure Generation for Intelligent Education
185. ICML 2026CSPO: Constraint-Sensitive Policy Optimization for Safe Reinforcement Learning
186. ICML 2026Curating the Future: A Scalable Recipe for Training Open-Ended Forecasters
187. ICML 2026Curriculum Reinforcement Learning for Black-Box Prompt Tuning via Large Language Models
188. ICML 2026D-ARL: A Distribution-Matched Asynchronous Reinforcement Learning Framework for Language Reasoning
189. ICML 2026D-CORE: Incentivizing Task Decomposition in Large Reasoning Models for Complex Tool Use
190. ICML 2026d2: Improving Reasoning in Diffusion Language Models via Trajectory Likelihood Estimation
191. ICML 2026D²Evo: Dual Difficulty-Aware Self-Evolution for Data-Efficient Reinforcement Learning
192. ICML 2026DADP: Domain Adaptive Diffusion Policy
193. ICML 2026DARTS: Distribution-Aware Active Rollout Trajectory Shaping for Accelerating LLM Reinforcement Learning
194. ICML 2026Data- and Variance-dependent Regret Bounds for Online Tabular MDPs
195. ICML 2026De-attribute to Forget for LLM Unlearning
196. ICML 2026Debate2Create: Robot Co-design via Multi-Agent LLM Debate
197. ICML 2026Debiased Model-based Representations for Sample-efficient Continuous Control
198. ICML 2026DecAEvolve: Decompose, Adapt, and Evolve for Effective LLM-based Scientific Equation Discovery
199. ICML 2026Decentralized and Disentangled Task–Role Representation Learning for Generalizable Offline Multi-Agent Meta Reinforcement Learning
200. ICML 2026Decision Transformers As Zero-Shot Learners via Text-Behavior Alignment

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.