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 1 of 10

1. NeurIPS 2023“Why Not Looking backward?” A Robust Two-Step Method to Automatically Terminate Bayesian Optimization
2. NeurIPS 2023$\texttt{TACO}$: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning
3. NeurIPS 2023A Definition of Continual Reinforcement Learning
4. NeurIPS 2023A Long $N$-step Surrogate Stage Reward for Deep Reinforcement Learning
5. NeurIPS 2023A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence
6. NeurIPS 2023A Partially-Supervised Reinforcement Learning Framework for Visual Active Search
7. NeurIPS 2023A Reduction-based Framework for Sequential Decision Making with Delayed Feedback
8. NeurIPS 2023A Robust and Opponent-Aware League Training Method for StarCraft II
9. NeurIPS 2023A Simple Solution for Offline Imitation from Observations and Examples with Possibly Incomplete Trajectories
10. NeurIPS 2023A State Representation for Diminishing Rewards
11. NeurIPS 2023A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes
12. NeurIPS 2023A Toolkit for Reliable Benchmarking and Research in Multi-Objective Reinforcement Learning
13. NeurIPS 2023A Trichotomy for Transductive Online Learning
14. NeurIPS 2023A Unified Algorithm Framework for Unsupervised Discovery of Skills based on Determinantal Point Process
15. NeurIPS 2023Accelerating Exploration with Unlabeled Prior Data
16. NeurIPS 2023Accelerating Monte Carlo Tree Search with Probability Tree State Abstraction
17. NeurIPS 2023Accelerating Reinforcement Learning with Value-Conditional State Entropy Exploration
18. NeurIPS 2023Accelerating Value Iteration with Anchoring
19. NeurIPS 2023Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples
20. NeurIPS 2023Action Inference by Maximising Evidence: Zero-Shot Imitation from Observation with World Models
21. NeurIPS 2023Active Observing in Continuous-time Control
22. NeurIPS 2023Active Vision Reinforcement Learning under Limited Visual Observability
23. NeurIPS 2023Adaptive Online Replanning with Diffusion Models
24. NeurIPS 2023Adjustable Robust Reinforcement Learning for Online 3D Bin Packing
25. NeurIPS 2023Adversarial Counterfactual Environment Model Learning
26. NeurIPS 2023Adversarial Model for Offline Reinforcement Learning
27. NeurIPS 2023AlberDICE: Addressing Out-Of-Distribution Joint Actions in Offline Multi-Agent RL via Alternating Stationary Distribution Correction Estimation
28. NeurIPS 2023Aligning Language Models with Human Preferences via a Bayesian Approach
29. NeurIPS 2023AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback
30. NeurIPS 2023An Alternating Optimization Method for Bilevel Problems under the Polyak-Łojasiewicz Condition
31. NeurIPS 2023An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient
32. NeurIPS 2023An Improved Relaxation for Oracle-Efficient Adversarial Contextual Bandits
33. NeurIPS 2023Anytime-Competitive Reinforcement Learning with Policy Prior
34. NeurIPS 2023Arbitrarily Scalable Environment Generators via Neural Cellular Automata
35. NeurIPS 2023Automatic Grouping for Efficient Cooperative Multi-Agent Reinforcement Learning
36. NeurIPS 2023AVIDa-hIL6: A Large-Scale VHH Dataset Produced from an Immunized Alpaca for Predicting Antigen-Antibody Interactions
37. NeurIPS 2023Bayesian Learning of Optimal Policies in Markov Decision Processes with Countably Infinite State-Space
38. NeurIPS 2023Bayesian Learning via Q-Exponential Process
39. NeurIPS 2023Bayesian Risk-Averse Q-Learning with Streaming Observations
40. NeurIPS 2023BeaverTails: Towards Improved Safety Alignment of LLM via a Human-Preference Dataset
41. NeurIPS 2023Behavior Alignment via Reward Function Optimization
42. NeurIPS 2023Belief Projection-Based Reinforcement Learning for Environments with Delayed Feedback
43. NeurIPS 2023Beyond Average Return in Markov Decision Processes
44. NeurIPS 2023Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence
45. NeurIPS 2023Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets
46. NeurIPS 2023Bi-Level Offline Policy Optimization with Limited Exploration
47. NeurIPS 2023Bilevel Coreset Selection in Continual Learning: A New Formulation and Algorithm
48. NeurIPS 2023BIRD: Generalizable Backdoor Detection and Removal for Deep Reinforcement Learning
49. NeurIPS 2023Blockwise Parallel Transformers for Large Context Models
50. NeurIPS 2023Boosting Verification of Deep Reinforcement Learning via Piece-Wise Linear Decision Neural Networks

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.