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

466 papers, page 4 of 10

151. NeurIPS 2024Few-Shot Task Learning through Inverse Generative Modeling
152. NeurIPS 2024Finding good policies in average-reward Markov Decision Processes without prior knowledge
153. NeurIPS 2024Fine Tuning Out-of-Vocabulary Item Recommendation with User Sequence Imagination
154. NeurIPS 2024Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning
155. NeurIPS 2024First-Explore, then Exploit: Meta-Learning to Solve Hard Exploration-Exploitation Trade-Offs
156. NeurIPS 2024FLAME : Factuality-Aware Alignment for Large Language Models
157. NeurIPS 2024FlexPlanner: Flexible 3D Floorplanning via Deep Reinforcement Learning in Hybrid Action Space with Multi-Modality Representation
158. NeurIPS 2024Flipping-based Policy for Chance-Constrained Markov Decision Processes
159. NeurIPS 2024Focus On What Matters: Separated Models For Visual-Based RL Generalization
160. NeurIPS 2024Foundations of Multivariate Distributional Reinforcement Learning
161. NeurIPS 2024From Text to Trajectory: Exploring Complex Constraint Representation and Decomposition in Safe Reinforcement Learning
162. NeurIPS 2024Functional Bilevel Optimization for Machine Learning
163. NeurIPS 2024GarmentLab: A Unified Simulation and Benchmark for Garment Manipulation
164. NeurIPS 2024Generalizing Consistency Policy to Visual RL with Prioritized Proximal Experience Regularization
165. NeurIPS 2024Generating Code World Models with Large Language Models Guided by Monte Carlo Tree Search
166. NeurIPS 2024GenRL: Multimodal-foundation world models for generalization in embodied agents
167. NeurIPS 2024Geometric-Averaged Preference Optimization for Soft Preference Labels
168. NeurIPS 2024Getting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT for LLM Alignment
169. NeurIPS 2024Goal Conditioned Reinforcement Learning for Photo Finishing Tuning
170. NeurIPS 2024Goal-Conditioned On-Policy Reinforcement Learning
171. NeurIPS 2024Going Beyond Heuristics by Imposing Policy Improvement as a Constraint
172. NeurIPS 2024GOMAA-Geo: GOal Modality Agnostic Active Geo-localization
173. NeurIPS 2024Gradient Cuff: Detecting Jailbreak Attacks on Large Language Models by Exploring Refusal Loss Landscapes
174. NeurIPS 2024Gradient-Free Methods for Nonconvex Nonsmooth Stochastic Compositional Optimization
175. NeurIPS 2024Graph Diffusion Policy Optimization
176. NeurIPS 2024Graph Learning for Numeric Planning
177. NeurIPS 2024Grounded Answers for Multi-agent Decision-making Problem through Generative World Model
178. NeurIPS 2024Grounding Multimodal Large Language Models in Actions
179. NeurIPS 2024Group Robust Preference Optimization in Reward-free RLHF
180. NeurIPS 2024GTA: Generative Trajectory Augmentation with Guidance for Offline Reinforcement Learning
181. NeurIPS 2024GUIDE: Real-Time Human-Shaped Agents
182. NeurIPS 2024Hierarchical Programmatic Option Framework
183. NeurIPS 2024How does Inverse RL Scale to Large State Spaces? A Provably Efficient Approach
184. NeurIPS 2024How to Solve Contextual Goal-Oriented Problems with Offline Datasets?
185. NeurIPS 2024HumanVLA: Towards Vision-Language Directed Object Rearrangement by Physical Humanoid
186. NeurIPS 2024Hybrid Reinforcement Learning Breaks Sample Size Barriers In Linear MDPs
187. NeurIPS 2024Identifying Latent State-Transition Processes for Individualized Reinforcement Learning
188. NeurIPS 2024Identifying Selections for Unsupervised Subtask Discovery
189. NeurIPS 2024Imitating Language via Scalable Inverse Reinforcement Learning
190. NeurIPS 2024Implicit Curriculum in Procgen Made Explicit
191. NeurIPS 2024Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn
192. NeurIPS 2024Improving Environment Novelty Quantification for Effective Unsupervised Environment Design
193. NeurIPS 2024In-Trajectory Inverse Reinforcement Learning: Learn Incrementally Before an Ongoing Trajectory Terminates
194. NeurIPS 2024Incremental Learning of Retrievable Skills For Efficient Continual Task Adaptation
195. NeurIPS 2024InfoRM: Mitigating Reward Hacking in RLHF via Information-Theoretic Reward Modeling
196. NeurIPS 2024Integrating Suboptimal Human Knowledge with Hierarchical Reinforcement Learning for Large-Scale Multiagent Systems
197. NeurIPS 2024Interpretable Concept Bottlenecks to Align Reinforcement Learning Agents
198. NeurIPS 2024Interpreting Learned Feedback Patterns in Large Language Models
199. NeurIPS 2024Is Behavior Cloning All You Need? Understanding Horizon in Imitation Learning
200. NeurIPS 2024Is Mamba Compatible with Trajectory Optimization in Offline Reinforcement 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.