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

1,021 papers, page 1 of 21

1. ICML 2026“very likely” Means “uncertain”? How LLMs Diverge from Humans in Linguistic Uncertainty Quantification
2. ICML 2026$\text{DT}^\text{2}$: Decision-Targeted Digital Twins
3. ICML 2026$\textit{S}$-SPPO: Semantic-Calibrated Self-Play Preference Optimization
4. ICML 2026$\texttt{Multi}^2$: Hierarchical Multi-Agent Decision-Making with LLM-Based Agents in Interactive Environments
5. ICML 2026$f$-Divergence Regularized RLHF: Two Tales of Sampling and Unified Analyses
6. ICML 2026$f$-Trajectory Balance: A Loss Family for Tuning GFlowNets, Generative Models, and LLMs with Off- and On-Policy Data
7. ICML 20263D-RFT: Reinforcement Fine-Tuning for Video-based 3D Scene Understanding
8. ICML 2026A Generalist Pair-wise Progress Critic Model for Vision-Language-Action Robots
9. ICML 2026A KL-regularization framework for learning to plan with adaptive priors
10. ICML 2026A Regret Minimization Framework on Preference Learning in Large Language Models
11. ICML 2026A Solver-Free Training Method for Predict-then-Optimize
12. ICML 2026AC-ODM: Actor–Critic Online Data Mixing for Sample-Efficient LLM Pretraining
13. ICML 2026Accelerating Q-learning through Efficient Value-Sharing across Actions
14. ICML 2026Accordion-Thinking: Self-Regulated Step Summaries for Efficient and Readable LLM Reasoning
15. ICML 2026Achieving Logarithmic Regret in KL-Regularized Zero-Sum Markov Games
16. ICML 2026ACTG-ARL: Differentially Private Conditional Text Generation with RL-Boosted Control
17. ICML 2026Action Manifold Smoothing: A Lipschitz Pathway Perspective on High-Dimensional Reinforcement Learning
18. ICML 2026Action-Sufficient Goal Representations
19. ICML 2026Active Attacks: Red-teaming LLMs via Adaptive Environments
20. ICML 2026Active Curriculum Refinement for Reinforcement Learning
21. ICML 2026Active Exploring like a Pigeon: Reinforcing Spatial Reasoning via Agentic Vision-Language Models
22. ICML 2026Active Policy Optimization for Individualized Dosing via Gradient Variance Minimization
23. ICML 2026ACTIVE-o3 : Empowering MLLMs with Active Perception via Pure Reinforcement Learning
24. ICML 2026ActiveUltraFeedback: Efficient Preference Data Generation using Active Learning
25. ICML 2026AdamO: A Collapse-Suppressed Optimizer for Offline RL
26. ICML 2026Adaptive Code Watermarking Through Reinforcement Learning
27. ICML 2026Adaptive Multi-Round Allocation with Stochastic Arrivals
28. ICML 2026Adaptive Policy Backbone via Shared Network
29. ICML 2026Adaptive Quasimetric Mapping : Principled Topological Abstraction for Robust Offline Goal-Conditioned Navigation
30. ICML 2026Adaptive Reinforcement Learning for Unobservable Random Delays
31. ICML 2026Adaptive Time Series Reasoning via Segment Selection
32. ICML 2026Addressing Semantic Blind Spots in Text-to-SQL via Component Pre-generation and AST Matching Rewards
33. ICML 2026Advancing LLM Reasoning with Natural Language and Numerical Feedback
34. ICML 2026Advantage Collapse in Group Relative Policy Optimization: Diagnosis and Mitigation
35. ICML 2026Advantage Weighted Matching: Aligning RL with Pretraining in Diffusion Models
36. ICML 2026Adversarial Dual On-Policy Distillation from Expressive Teacher
37. ICML 2026Adversarial Reinforcement Learning for Robust Diffusion Large Language Model Unlearning
38. ICML 2026AdvEvo-MARL: Shaping Internalized Safety through Adversarial Co-Evolution in Multi-Agent Reinforcement Learning
39. ICML 2026Agent Learning via Early Experience
40. ICML 2026Agent-Omit: Adaptive Context Omission for Efficient LLM Agents
41. ICML 2026Agent0-VL: Exploring Self-Evolving Agent for Tool-Integrated Vision-Language Reasoning
42. ICML 2026AgentConductor: Topology Evolution for Multi-Agent Competition-Level Code Generation
43. ICML 2026Agentic Monte Carlo: Simulating Reinforcement Learning for Black-Box Agents
44. ICML 2026Alignment Risks from Capability-Seeking RL Training
45. ICML 2026Alignment Tampering: How Reinforcement Learning from Human Feedback Is Exploited to Optimize Misaligned Biases
46. ICML 2026Alignment-Guided Score Matching for Text-to-Image Alignment in Diffusion Models
47. ICML 2026AlphaGRPO: Unlocking Self-Reflective Multimodal Generation in Unified Multimodal Models via Decompositional Verifiable Reward
48. ICML 2026AlphaRouter: Token-level Routing Between SLM and LLM with Reinforcement Learning and Tree Search
49. ICML 2026ALSO: Adversarial Online Strategy Optimization for Social Agents
50. ICML 2026Alternating Reinforcement Learning for Rubric-Based Reward Modeling in Non-Verifiable LLM Post-Training

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.