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

1,190 papers, page 4 of 24

151. ICLR 2024Entity-Centric Reinforcement Learning for Object Manipulation from Pixels
152. ICLR 2024Eureka: Human-Level Reward Design via Coding Large Language Models
153. ICLR 2024Explaining Kernel Clustering via Decision Trees
154. ICLR 2024Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning
155. ICLR 2024Exploring the Promise and Limits of Real-Time Recurrent Learning
156. ICLR 2024Fast Hyperboloid Decision Tree Algorithms
157. ICLR 2024Fast Imitation via Behavior Foundation Models
158. ICLR 2024Fast Value Tracking for Deep Reinforcement Learning
159. ICLR 2024Federated Q-Learning: Linear Regret Speedup with Low Communication Cost
160. ICLR 2024Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning
161. ICLR 2024First-order ANIL provably learns representations despite overparametrisation
162. ICLR 2024FLD: Fourier Latent Dynamics for Structured Motion Representation and Learning
163. ICLR 2024Flow to Better: Offline Preference-based Reinforcement Learning via Preferred Trajectory Generation
164. ICLR 2024Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning
165. ICLR 2024Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations
166. ICLR 2024Goodhart's Law in Reinforcement Learning
167. ICLR 2024GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher
168. ICLR 2024H-GAP: Humanoid Control with a Generalist Planner
169. ICLR 2024Harnessing Density Ratios for Online Reinforcement Learning
170. ICLR 2024HAZARD Challenge: Embodied Decision Making in Dynamically Changing Environments
171. ICLR 2024Hindsight PRIORs for Reward Learning from Human Preferences
172. ICLR 2024Horizon-Free Regret for Linear Markov Decision Processes
173. ICLR 2024Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs
174. ICLR 2024Hybrid Internal Model: Learning Agile Legged Locomotion with Simulated Robot Response
175. ICLR 2024Identifying Policy Gradient Subspaces
176. ICLR 2024Illusory Attacks: Information-theoretic detectability matters in adversarial attacks
177. ICLR 2024Imitation Learning from Observation with Automatic Discount Scheduling
178. ICLR 2024Impact of Computation in Integral Reinforcement Learning for Continuous-Time Control
179. ICLR 2024Improved Efficiency Based on Learned Saccade and Continuous Scene Reconstruction From Foveated Visual Sampling
180. ICLR 2024Improving Generalization of Alignment with Human Preferences through Group Invariant Learning
181. ICLR 2024Improving Intrinsic Exploration by Creating Stationary Objectives
182. ICLR 2024Improving Offline RL by Blending Heuristics
183. ICLR 2024In-context Exploration-Exploitation for Reinforcement Learning
184. ICLR 2024Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions
185. ICLR 2024Integrating Planning and Deep Reinforcement Learning via Automatic Induction of Task Substructures
186. ICLR 2024Intelligent Switching for Reset-Free RL
187. ICLR 2024Interpretable Meta-Learning of Physical Systems
188. ICLR 2024Jumanji: a Diverse Suite of Scalable Reinforcement Learning Environments in JAX
189. ICLR 2024Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies
190. ICLR 2024L2P-MIP: Learning to Presolve for Mixed Integer Programming
191. ICLR 2024Language Control Diffusion: Efficiently Scaling through Space, Time, and Tasks
192. ICLR 2024Language Model Detectors Are Easily Optimized Against
193. ICLR 2024Language Model Self-improvement by Reinforcement Learning Contemplation
194. ICLR 2024Large Language Models as Generalizable Policies for Embodied Tasks
195. ICLR 2024Learning Decentralized Partially Observable Mean Field Control for Artificial Collective Behavior
196. ICLR 2024Learning Energy Decompositions for Partial Inference in GFlowNets
197. ICLR 2024Learning from Sparse Offline Datasets via Conservative Density Estimation
198. ICLR 2024Learning Hierarchical World Models with Adaptive Temporal Abstractions from Discrete Latent Dynamics
199. ICLR 2024Learning Interactive Real-World Simulators
200. ICLR 2024Learning Mean Field Games on Sparse Graphs: A Hybrid Graphex Approach

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.