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 5 of 10

201. NeurIPS 2024Is O(log N) practical? Near-Equivalence Between Delay Robustness and Bounded Regret in Bandits and RL
202. NeurIPS 2024Is Value Learning Really the Main Bottleneck in Offline RL?
203. NeurIPS 2024Iteratively Refined Behavior Regularization for Offline Reinforcement Learning
204. NeurIPS 2024iVideoGPT: Interactive VideoGPTs are Scalable World Models
205. NeurIPS 2024JaxMARL: Multi-Agent RL Environments and Algorithms in JAX
206. NeurIPS 2024Kaleidoscope: Learnable Masks for Heterogeneous Multi-agent Reinforcement Learning
207. NeurIPS 2024KALM: Knowledgeable Agents by Offline Reinforcement Learning from Large Language Model Rollouts
208. NeurIPS 2024Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm
209. NeurIPS 2024Language Grounded Multi-agent Reinforcement Learning with Human-interpretable Communication
210. NeurIPS 2024Large Language Models Play StarCraft II:Benchmarks and A Chain of Summarization Approach
211. NeurIPS 2024Last-Iterate Global Convergence of Policy Gradients for Constrained Reinforcement Learning
212. NeurIPS 2024Latent Learning Progress Drives Autonomous Goal Selection in Human Reinforcement Learning
213. NeurIPS 2024Latent Plan Transformer for Trajectory Abstraction: Planning as Latent Space Inference
214. NeurIPS 2024Learning an Actionable Discrete Diffusion Policy via Large-Scale Actionless Video Pre-Training
215. NeurIPS 2024Learning Distinguishable Trajectory Representation with Contrastive Loss
216. NeurIPS 2024Learning Equilibria in Adversarial Team Markov Games: A Nonconvex-Hidden-Concave Min-Max Optimization Problem
217. NeurIPS 2024Learning Formal Mathematics From Intrinsic Motivation
218. NeurIPS 2024Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate
219. NeurIPS 2024Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm
220. NeurIPS 2024Learning Goal-Conditioned Representations for Language Reward Models
221. NeurIPS 2024Learning in Markov Games with Adaptive Adversaries: Policy Regret, Fundamental Barriers, and Efficient Algorithms
222. NeurIPS 2024Learning Multimodal Behaviors from Scratch with Diffusion Policy Gradient
223. NeurIPS 2024Learning Successor Features the Simple Way
224. NeurIPS 2024Learning to Assist Humans without Inferring Rewards
225. NeurIPS 2024Learning to Balance Altruism and Self-interest Based on Empathy in Mixed-Motive Games
226. NeurIPS 2024Learning to Cooperate with Humans using Generative Agents
227. NeurIPS 2024Learning to Discuss Strategically: A Case Study on One Night Ultimate Werewolf
228. NeurIPS 2024Learning Versatile Skills with Curriculum Masking
229. NeurIPS 2024Learning World Models for Unconstrained Goal Navigation
230. NeurIPS 2024LeDex: Training LLMs to Better Self-Debug and Explain Code
231. NeurIPS 2024Leveraging Separated World Model for Exploration in Visually Distracted Environments
232. NeurIPS 2024LLM-based Skill Diffusion for Zero-shot Policy Adaptation
233. NeurIPS 2024Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs
234. NeurIPS 2024Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning
235. NeurIPS 2024MADiff: Offline Multi-agent Learning with Diffusion Models
236. NeurIPS 2024Make-An-Agent: A Generalizable Policy Network Generator with Behavior-Prompted Diffusion
237. NeurIPS 2024Making Offline RL Online: Collaborative World Models for Offline Visual Reinforcement Learning
238. NeurIPS 2024Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models
239. NeurIPS 2024Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow
240. NeurIPS 2024Measuring Goal-Directedness
241. NeurIPS 2024Measuring Mutual Policy Divergence for Multi-Agent Sequential Exploration
242. NeurIPS 2024Melting Pot Contest: Charting the Future of Generalized Cooperative Intelligence
243. NeurIPS 2024MeMo: Meaningful, Modular Controllers via Noise Injection
244. NeurIPS 2024Meta-Controller: Few-Shot Imitation of Unseen Embodiments and Tasks in Continuous Control
245. NeurIPS 2024Meta-DT: Offline Meta-RL as Conditional Sequence Modeling with World Model Disentanglement
246. NeurIPS 2024Meta-Reinforcement Learning with Universal Policy Adaptation: Provable Near-Optimality under All-task Optimum Comparator
247. NeurIPS 2024MetaCURL: Non-stationary Concave Utility Reinforcement Learning
248. NeurIPS 2024Mimicking To Dominate: Imitation Learning Strategies for Success in Multiagent Games
249. NeurIPS 2024Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning
250. NeurIPS 2024Minimum Entropy Coupling with Bottleneck

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.