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

484 papers, page 4 of 10

151. NeurIPS 2023Extracting Reward Functions from Diffusion Models
152. NeurIPS 2023f-Policy Gradients: A General Framework for Goal-Conditioned RL using f-Divergences
153. NeurIPS 2023Face Reconstruction from Facial Templates by Learning Latent Space of a Generator Network
154. NeurIPS 2023Facing Off World Model Backbones: RNNs, Transformers, and S4
155. NeurIPS 2023FAMO: Fast Adaptive Multitask Optimization
156. NeurIPS 2023Fast Bellman Updates for Wasserstein Distributionally Robust MDPs
157. NeurIPS 2023Feature Learning for Interpretable, Performant Decision Trees
158. NeurIPS 2023Finding Counterfactually Optimal Action Sequences in Continuous State Spaces
159. NeurIPS 2023Finding Safe Zones of Markov Decision Processes Policies
160. NeurIPS 2023Fine-Grained Human Feedback Gives Better Rewards for Language Model Training
161. NeurIPS 2023Finite-Time Analysis of Single-Timescale Actor-Critic
162. NeurIPS 2023First- and Second-Order Bounds for Adversarial Linear Contextual Bandits
163. NeurIPS 2023Fixing the NTK: From Neural Network Linearizations to Exact Convex Programs
164. NeurIPS 2023Flexible Attention-Based Multi-Policy Fusion for Efficient Deep Reinforcement Learning
165. NeurIPS 2023FlowPG: Action-constrained Policy Gradient with Normalizing Flows
166. NeurIPS 2023For SALE: State-Action Representation Learning for Deep Reinforcement Learning
167. NeurIPS 2023Fractal Landscapes in Policy Optimization
168. NeurIPS 2023From Pixels to UI Actions: Learning to Follow Instructions via Graphical User Interfaces
169. NeurIPS 2023Future-Dependent Value-Based Off-Policy Evaluation in POMDPs
170. NeurIPS 2023Game Solving with Online Fine-Tuning
171. NeurIPS 2023General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence
172. NeurIPS 2023Generalized Weighted Path Consistency for Mastering Atari Games
173. NeurIPS 2023Generating Behaviorally Diverse Policies with Latent Diffusion Models
174. NeurIPS 2023Generative Modelling of Stochastic Actions with Arbitrary Constraints in Reinforcement Learning
175. NeurIPS 2023Generator Born from Classifier
176. NeurIPS 2023Gigastep - One Billion Steps per Second Multi-agent Reinforcement Learning
177. NeurIPS 2023Global Identifiability of $\ell_1$-based Dictionary Learning via Matrix Volume Optimization
178. NeurIPS 2023Goal-conditioned Offline Planning from Curious Exploration
179. NeurIPS 2023Goal-Conditioned Predictive Coding for Offline Reinforcement Learning
180. NeurIPS 2023Gradient Informed Proximal Policy Optimization
181. NeurIPS 2023Guide Your Agent with Adaptive Multimodal Rewards
182. NeurIPS 2023Guiding Large Language Models via Directional Stimulus Prompting
183. NeurIPS 2023H-InDex: Visual Reinforcement Learning with Hand-Informed Representations for Dexterous Manipulation
184. NeurIPS 2023Harnessing the power of choices in decision tree learning
185. NeurIPS 2023Hierarchical Adaptive Value Estimation for Multi-modal Visual Reinforcement Learning
186. NeurIPS 2023Hierarchical Multi-Agent Skill Discovery
187. NeurIPS 2023HIQL: Offline Goal-Conditioned RL with Latent States as Actions
188. NeurIPS 2023Hokoff: Real Game Dataset from Honor of Kings and its Offline Reinforcement Learning Benchmarks
189. NeurIPS 2023Honesty Is the Best Policy: Defining and Mitigating AI Deception
190. NeurIPS 2023How to Fine-tune the Model: Unified Model Shift and Model Bias Policy Optimization
191. NeurIPS 2023Hybrid Policy Optimization from Imperfect Demonstrations
192. NeurIPS 2023Hybrid Search for Efficient Planning with Completeness Guarantees
193. NeurIPS 2023Hyperbolic Space with Hierarchical Margin Boosts Fine-Grained Learning from Coarse Labels
194. NeurIPS 2023Hyperbolic VAE via Latent Gaussian Distributions
195. NeurIPS 2023Hypervolume Maximization: A Geometric View of Pareto Set Learning
196. NeurIPS 2023Imitation Learning from Imperfection: Theoretical Justifications and Algorithms
197. NeurIPS 2023Imitation Learning from Vague Feedback
198. NeurIPS 2023IMP-MARL: a Suite of Environments for Large-scale Infrastructure Management Planning via MARL
199. NeurIPS 2023Importance Weighted Actor-Critic for Optimal Conservative Offline Reinforcement Learning
200. NeurIPS 2023Importance-aware Co-teaching for Offline Model-based Optimization

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.