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 1 of 10

1. NeurIPS 2024A Critical Evaluation of AI Feedback for Aligning Large Language Models
2. NeurIPS 2024A Method for Evaluating Hyperparameter Sensitivity in Reinforcement Learning
3. NeurIPS 2024A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation
4. NeurIPS 2024A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics
5. NeurIPS 2024A Simple Framework for Generalization in Visual RL under Dynamic Scene Perturbations
6. NeurIPS 2024A Simulation Benchmark for Autonomous Racing with Large-Scale Human Data
7. NeurIPS 2024A Structure-Aware Framework for Learning Device Placements on Computation Graphs
8. NeurIPS 2024A Study of Plasticity Loss in On-Policy Deep Reinforcement Learning
9. NeurIPS 2024A theoretical case-study of Scalable Oversight in Hierarchical Reinforcement Learning
10. NeurIPS 2024A Tractable Inference Perspective of Offline RL
11. NeurIPS 2024A Unified Principle of Pessimism for Offline Reinforcement Learning under Model Mismatch
12. NeurIPS 2024A2PO: Towards Effective Offline Reinforcement Learning from an Advantage-aware Perspective
13. NeurIPS 2024Abstract Reward Processes: Leveraging State Abstraction for Consistent Off-Policy Evaluation
14. NeurIPS 2024Achieving $\tilde{O}(1/\epsilon)$ Sample Complexity for Constrained Markov Decision Process
15. NeurIPS 2024Achieving Constant Regret in Linear Markov Decision Processes
16. NeurIPS 2024Achieving Tractable Minimax Optimal Regret in Average Reward MDPs
17. NeurIPS 2024Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning
18. NeurIPS 2024Adam on Local Time: Addressing Nonstationarity in RL with Relative Adam Timesteps
19. NeurIPS 2024Adaptive $Q$-Aid for Conditional Supervised Learning in Offline Reinforcement Learning
20. NeurIPS 2024Adaptive Exploration for Data-Efficient General Value Function Evaluations
21. NeurIPS 2024Adaptive Labeling for Efficient Out-of-distribution Model Evaluation
22. NeurIPS 2024Adaptive Preference Scaling for Reinforcement Learning with Human Feedback
23. NeurIPS 2024AdaptiveISP: Learning an Adaptive Image Signal Processor for Object Detection
24. NeurIPS 2024AdaSociety: An Adaptive Environment with Social Structures for Multi-Agent Decision-Making
25. NeurIPS 2024ADOPT: Modified Adam Can Converge with Any $\beta_2$ with the Optimal Rate
26. NeurIPS 2024Adversarial Environment Design via Regret-Guided Diffusion Models
27. NeurIPS 2024Adversarially Robust Decision Transformer
28. NeurIPS 2024Adversarially Trained Weighted Actor-Critic for Safe Offline Reinforcement Learning
29. NeurIPS 2024AGILE: A Novel Reinforcement Learning Framework of LLM Agents
30. NeurIPS 2024Aligner: Efficient Alignment by Learning to Correct
31. NeurIPS 2024Aligning Diffusion Behaviors with Q-functions for Efficient Continuous Control
32. NeurIPS 2024Aligning Individual and Collective Objectives in Multi-Agent Cooperation
33. NeurIPS 2024Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization
34. NeurIPS 2024Aligning Vision Models with Human Aesthetics in Retrieval: Benchmarks and Algorithms
35. NeurIPS 2024Alignment at Pre-training! Towards Native Alignment for Arabic LLMs
36. NeurIPS 2024AMAGO-2: Breaking the Multi-Task Barrier in Meta-Reinforcement Learning with Transformers
37. NeurIPS 2024Amnesia as a Catalyst for Enhancing Black Box Pixel Attacks in Image Classification and Object Detection
38. NeurIPS 2024Amortized Active Causal Induction with Deep Reinforcement Learning
39. NeurIPS 2024Amortizing intractable inference in diffusion models for vision, language, and control
40. NeurIPS 2024An Analytical Study of Utility Functions in Multi-Objective Reinforcement Learning
41. NeurIPS 2024An Efficient High-dimensional Gradient Estimator for Stochastic Differential Equations
42. NeurIPS 2024An Offline Adaptation Framework for Constrained Multi-Objective Reinforcement Learning
43. NeurIPS 2024Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning
44. NeurIPS 2024Assouad, Fano, and Le Cam with Interaction: A Unifying Lower Bound Framework and Characterization for Bandit Learnability
45. NeurIPS 2024AuctionNet: A Novel Benchmark for Decision-Making in Large-Scale Games
46. NeurIPS 2024Automated Multi-level Preference for MLLMs
47. NeurIPS 2024Autoregressive Policy Optimization for Constrained Allocation Tasks
48. NeurIPS 2024Axioms for AI Alignment from Human Feedback
49. NeurIPS 2024Balancing Context Length and Mixing Times for Reinforcement Learning at Scale
50. NeurIPS 2024Beating Adversarial Low-Rank MDPs with Unknown Transition and Bandit Feedback

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.