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

2,079 papers, page 25 of 42

1201. ICML 2025LARM: Large Auto-Regressive Model for Long-Horizon Embodied Intelligence
1202. ICML 2025Latent Action Learning Requires Supervision in the Presence of Distractors
1203. ICML 2025Layer-wise Alignment: Examining Safety Alignment Across Image Encoder Layers in Vision Language Models
1204. ICML 2025LBI-FL: Low-Bit Integerized Federated Learning with Temporally Dynamic Bit-Width Allocation
1205. ICML 2025Learning Dynamics under Environmental Constraints via Measurement-Induced Bundle Structures
1206. ICML 2025Learning from Suboptimal Data in Continuous Control via Auto-Regressive Soft Q-Network
1207. ICML 2025Learning Fused State Representations for Control from Multi-View Observations
1208. ICML 2025Learning Mean Field Control on Sparse Graphs
1209. ICML 2025Learning Policy Committees for Effective Personalization in MDPs with Diverse Tasks
1210. ICML 2025Learning Progress Driven Multi-Agent Curriculum
1211. ICML 2025Learning to Reuse Policies in State Evolvable Environments
1212. ICML 2025Learning to Trust Bellman Updates: Selective State-Adaptive Regularization for Offline RL
1213. ICML 2025Learning Utilities from Demonstrations in Markov Decision Processes
1214. ICML 2025Learning with Selectively Labeled Data from Multiple Decision-makers
1215. ICML 2025Leveraging Offline Data in Linear Latent Contextual Bandits
1216. ICML 2025Leveraging Skills from Unlabeled Prior Data for Efficient Online Exploration
1217. ICML 2025Linear $Q$-Learning Does Not Diverge in $L^2$: Convergence Rates to a Bounded Set
1218. ICML 2025LineFlow: A Framework to Learn Active Control of Production Lines
1219. ICML 2025LipsNet++: Unifying Filter and Controller into a Policy Network
1220. ICML 2025LLM Alignment as Retriever Optimization: An Information Retrieval Perspective
1221. ICML 2025LLM-Assisted Semantically Diverse Teammate Generation for Efficient Multi-agent Coordination
1222. ICML 2025LLMs Can Reason Faster Only If We Let Them
1223. ICML 2025LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Models
1224. ICML 2025Local Manifold Approximation and Projection for Manifold-Aware Diffusion Planning
1225. ICML 2025Log-Sum-Exponential Estimator for Off-Policy Evaluation and Learning
1226. ICML 2025Logarithmic Regret for Online KL-Regularized Reinforcement Learning
1227. ICML 2025LOGO --- Long cOntext aliGnment via efficient preference Optimization
1228. ICML 2025M³HF: Multi-agent Reinforcement Learning from Multi-phase Human Feedback of Mixed Quality
1229. ICML 2025MARGE: Improving Math Reasoning with Guided Exploration
1230. ICML 2025Mastering Massive Multi-Task Reinforcement Learning via Mixture-of-Expert Decision Transformer
1231. ICML 2025Maximum Entropy Reinforcement Learning with Diffusion Policy
1232. ICML 2025Maximum Total Correlation Reinforcement Learning
1233. ICML 2025MENTOR: Mixture-of-Experts Network with Task-Oriented Perturbation for Visual Reinforcement Learning
1234. ICML 2025Meta-Black-Box-Optimization through Offline Q-function Learning
1235. ICML 2025Meta-Reinforcement Learning with Adaptation from Human Feedback via Preference-Order-Preserving Task Embedding
1236. ICML 2025Minimax Optimal Regret Bound for Reinforcement Learning with Trajectory Feedback
1237. ICML 2025Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn
1238. ICML 2025Model Immunization from a Condition Number Perspective
1239. ICML 2025Model-Based Exploration in Monitored Markov Decision Processes
1240. ICML 2025MODULI: Unlocking Preference Generalization via Diffusion Models for Offline Multi-Objective Reinforcement Learning
1241. ICML 2025MONA: Myopic Optimization with Non-myopic Approval Can Mitigate Multi-step Reward Hacking
1242. ICML 2025Monte Carlo Tree Diffusion for System 2 Planning
1243. ICML 2025MPO: An Efficient Post-Processing Framework for Mixing Diverse Preference Alignment
1244. ICML 2025Multi-objective Linear Reinforcement Learning with Lexicographic Rewards
1245. ICML 2025Multi-Session Budget Optimization for Forward Auction-based Federated Learning
1246. ICML 2025Multi-Stage Manipulation with Demonstration-Augmented Reward, Policy, and World Model Learning
1247. ICML 2025Multi-Timescale Dynamics Model Bayesian Optimization for Plasma Stabilization in Tokamaks
1248. ICML 2025Multi-Turn Code Generation Through Single-Step Rewards
1249. ICML 2025Multiple-policy Evaluation via Density Estimation
1250. ICML 2025Navigating the Social Welfare Frontier: Portfolios for Multi-objective 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.