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

784 papers, page 4 of 16

151. NeurIPS 2025DexGarmentLab: Dexterous Garment Manipulation Environment with Generalizable Policy
152. NeurIPS 2025Differentiable Decision Tree via "ReLU+Argmin" Reformulation
153. NeurIPS 2025Diffusion Guided Adversarial State Perturbations in Reinforcement Learning
154. NeurIPS 2025Diffusion Models Meet Contextual Bandits
155. NeurIPS 2025DisCO: Reinforcing Large Reasoning Models with Discriminative Constrained Optimization
156. NeurIPS 2025DISCOVER: Automated Curricula for Sparse-Reward Reinforcement Learning
157. NeurIPS 2025Distances for Markov chains from sample streams
158. NeurIPS 2025Diversifying Parallel Ergodic Search: A Signature Kernel Evolution Strategy
159. NeurIPS 2025Diversity-Aware Policy Optimization for Large Language Model Reasoning
160. NeurIPS 2025DMWM: Dual-Mind World Model with Long-Term Imagination
161. NeurIPS 2025Doctor Approved: Generating Medically Accurate Skin Disease Images through AI-Expert Feedback
162. NeurIPS 2025Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?
163. NeurIPS 2025Don’t Think Longer, Think Wisely: Optimizing Thinking Dynamics for Large Reasoning Models
164. NeurIPS 2025Don’t Trade Off Safety: Diffusion Regularization for Constrained Offline RL
165. NeurIPS 2025Doubly Robust Alignment for Large Language Models
166. NeurIPS 2025DriveDPO: Policy Learning via Safety DPO For End-to-End Autonomous Driving
167. NeurIPS 2025DualFocus: Depth from Focus with Spatio-Focal Dual Variational Constraints
168. NeurIPS 2025DyMoDreamer: World Modeling with Dynamic Modulation
169. NeurIPS 2025Dyn-O: Building Structured World Models with Object-Centric Representations
170. NeurIPS 2025DynaAct: Large Language Model Reasoning with Dynamic Action Spaces
171. NeurIPS 2025Dynamic Configuration for Cutting Plane Separators via Reinforcement Learning on Incremental Graph
172. NeurIPS 2025DynamicRAG: Leveraging Outputs of Large Language Model as Feedback for Dynamic Reranking in Retrieval-Augmented Generation
173. NeurIPS 2025Dynamics-Aligned Latent Imagination in Contextual World Models for Zero-Shot Generalization
174. NeurIPS 2025DynaRend: Learning 3D Dynamics via Masked Future Rendering for Robotic Manipulation
175. NeurIPS 2025EconGym: A Scalable AI Testbed with Diverse Economic Tasks
176. NeurIPS 2025EDELINE: Enhancing Memory in Diffusion-based World Models via Linear-Time Sequence Modeling
177. NeurIPS 2025Effective Policy Learning for Multi-Agent Online Coordination Beyond Submodular Objectives
178. NeurIPS 2025Efficient and Near-Optimal Algorithm for Contextual Dueling Bandits with Offline Regression Oracles
179. NeurIPS 2025Efficient Bayesian Experiment Design with Equivariant Networks
180. NeurIPS 2025Efficient Policy Optimization in Robust Constrained MDPs with Iteration Complexity Guarantees
181. NeurIPS 2025Efficient Preference-Based Reinforcement Learning: Randomized Exploration meets Experimental Design
182. NeurIPS 2025Efficient Safe Meta-Reinforcement Learning: Provable Near-Optimality and Anytime Safety
183. NeurIPS 2025EgoBridge: Domain Adaptation for Generalizable Imitation from Egocentric Human Data
184. NeurIPS 2025Elastic ViTs from Pretrained Models without Retraining
185. NeurIPS 2025Eliciting Reasoning in Language Models with Cognitive Tools
186. NeurIPS 2025Eluder dimension: localise it!
187. NeurIPS 2025Embodied Crowd Counting
188. NeurIPS 2025Emerging Risks from Embodied AI Require Urgent Policy Action
189. NeurIPS 2025Empirical Study on Robustness and Resilience in Cooperative Multi-Agent Reinforcement Learning
190. NeurIPS 2025Empowering Decision Trees via Shape Function Branching
191. NeurIPS 2025Enhancing Interpretability in Deep Reinforcement Learning through Semantic Clustering
192. NeurIPS 2025Enhancing Personalized Multi-Turn Dialogue with Curiosity Reward
193. NeurIPS 2025Enhancing Safety in Reinforcement Learning with Human Feedback via Rectified Policy Optimization
194. NeurIPS 2025Enhancing Tactile-based Reinforcement Learning for Robotic Control
195. NeurIPS 2025Enhancing the Outcome Reward-based RL Training of MLLMs with Self-Consistency Sampling
196. NeurIPS 2025Enigmata: Scaling Logical Reasoning in Large Language Models with Synthetic Verifiable Puzzles
197. NeurIPS 2025Equilibrium Policy Generalization: A Reinforcement Learning Framework for Cross-Graph Zero-Shot Generalization in Pursuit-Evasion Games
198. NeurIPS 2025ESCORT: Efficient Stein-variational and Sliced Consistency-Optimized Temporal Belief Representation for POMDPs
199. NeurIPS 2025Estimating cognitive biases with attention-aware inverse planning
200. NeurIPS 2025EVAAA: A Virtual Environment Platform for Essential Variables in Autonomous and Adaptive Agents

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.