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

784 papers, page 8 of 16

351. NeurIPS 2025Learning to Think: Information-Theoretic Reinforcement Fine-Tuning for LLMs
352. NeurIPS 2025Learning When to Think: Shaping Adaptive Reasoning in R1-Style Models via Multi-Stage RL
353. NeurIPS 2025Less is More: an Attention-free Sequence Prediction Modeling for Offline Embodied Learning
354. NeurIPS 2025Leveraging Conditional Dependence for Efficient World Model Denoising
355. NeurIPS 2025LILO: Learning to Reason at the Frontier of Learnability
356. NeurIPS 2025Linear Mixture Distributionally Robust Markov Decision Processes
357. NeurIPS 2025LLM-Explorer: A Plug-in Reinforcement Learning Policy Exploration Enhancement Driven by Large Language Models
358. NeurIPS 2025Logic.py: Bridging the Gap between LLMs and Constraint Solvers
359. NeurIPS 2025Look Before You Leap: A GUI-Critic-R1 Model for Pre-Operative Error Diagnosis in GUI Automation
360. NeurIPS 2025LOPT: Learning Optimal Pigovian Tax in Sequential Social Dilemmas
361. NeurIPS 2025MACS: Multi-Agent Reinforcement Learning for Optimization of Crystal Structures
362. NeurIPS 2025MALinZero: Efficient Low-Dimensional Search for Mastering Complex Multi-Agent Planning
363. NeurIPS 2025Markov Persuasion Processes: Learning to Persuade From Scratch
364. NeurIPS 2025Mean-Field Sampling for Cooperative Multi-Agent Reinforcement Learning
365. NeurIPS 2025Measure gradients, not activations! Enhancing neuronal activity in deep reinforcement learning
366. NeurIPS 2025Memo: Training Memory-Efficient Embodied Agents with Reinforcement Learning
367. NeurIPS 2025Memory-Enhanced Neural Solvers for Routing Problems
368. NeurIPS 2025Mesh-RFT: Enhancing Mesh Generation via Fine-grained Reinforcement Fine-Tuning
369. NeurIPS 2025Meta-learning how to Share Credit among Macro-Actions
370. NeurIPS 2025Meta-Learning Objectives for Preference Optimization
371. NeurIPS 2025Meta-World+: An Improved, Standardized, RL Benchmark
372. NeurIPS 2025MetaBox-v2: A Unified Benchmark Platform for Meta-Black-Box Optimization
373. NeurIPS 2025MetaKoopman: Bayesian Meta-Learning of Koopman Operators for Modeling Structured Dynamics under Distribution Shifts
374. NeurIPS 2025MiCo: Multi-image Contrast for Reinforcement Visual Reasoning
375. NeurIPS 2025Mind the Gap: Bridging Thought Leap for Improved Chain-of-Thought Tuning
376. NeurIPS 2025Mind the GAP! The Challenges of Scale in Pixel-based Deep Reinforcement Learning
377. NeurIPS 2025MindJourney: Test-Time Scaling with World Models for Spatial Reasoning
378. NeurIPS 2025MindOmni: Unleashing Reasoning Generation in Vision Language Models with RGPO
379. NeurIPS 2025MisoDICE: Multi-Agent Imitation from Mixed-Quality Demonstrations
380. NeurIPS 2025Mitigating Reward Over-optimization in Direct Alignment Algorithms with Importance Sampling
381. NeurIPS 2025Mixing Expert Knowledge: Bring Human Thoughts Back To the Game of Go
382. NeurIPS 2025Mixture-of-Experts Meets In-Context Reinforcement Learning
383. NeurIPS 2025MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge for Text-to-Image Generation?
384. NeurIPS 2025MLE-Dojo: Interactive Environments for Empowering LLM Agents in Machine Learning Engineering
385. NeurIPS 2025MMaDA: Multimodal Large Diffusion Language Models
386. NeurIPS 2025Model Selection for Off-policy Evaluation: New Algorithms and Experimental Protocol
387. NeurIPS 2025Model-Based Policy Adaptation for Closed-Loop End-to-end Autonomous Driving
388. NeurIPS 2025Modelling the control of offline processing with reinforcement learning
389. NeurIPS 2025MonoLift: Learning 3D Manipulation Policies from Monocular RGB via Distillation
390. NeurIPS 2025MOSDT: Self-Distillation-Based Decision Transformer for Multi-Agent Offline Safe Reinforcement Learning
391. NeurIPS 2025MRO: Enhancing Reasoning in Diffusion Language Models via Multi-Reward Optimization
392. NeurIPS 2025MTL-KD: Multi-Task Learning Via Knowledge Distillation for Generalizable Neural Vehicle Routing Solver
393. NeurIPS 2025MTRec: Learning to Align with User Preferences via Mental Reward Models
394. NeurIPS 2025Multi-Agent Collaboration via Evolving Orchestration
395. NeurIPS 2025Multi-Agent Imitation by Learning and Sampling from Factorized Soft Q-Function
396. NeurIPS 2025Multi-agent Markov Entanglement
397. NeurIPS 2025Multi-Agent Reinforcement Learning with Communication-Constrained Priors
398. NeurIPS 2025Multi-Objective Reinforcement Learning with Max-Min Criterion: A Game-Theoretic Approach
399. NeurIPS 2025Multi-step Visual Reasoning with Visual Tokens Scaling and Verification
400. NeurIPS 2025Multi-Task Vehicle Routing Solver via Mixture of Specialized Experts under State-Decomposable MDP

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.