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 14 of 21

651. ICML 2026Prioritize the Process, Not Just the Outcome: Rewarding Latent Thought Trajectories Improves Reasoning in Looped Language Models
652. ICML 2026Prioritized Model Experience Replay
653. ICML 2026PRISM: Demystifying Retention and Interaction in Mid-Training
654. ICML 2026Privileged Information Distillation for Language Models
655. ICML 2026PRM-PBE: Process Reward Model for Reinforcement Learning in Programming-by-Example
656. ICML 2026Probabilistic Performance Guarantees for Multi-Task Reinforcement Learning
657. ICML 2026Probing RLVR Training Instability through the Lens of Objective-Level Hacking
658. ICML 2026Procedural Generation Of Algorithm Discovery Tasks in Machine Learning
659. ICML 2026PromptPilot: Game-Theoretic Multi-Agent Prompt Optimization for Segment Anything
660. ICML 2026PromptRL: Prompt Matters in RL for Flow-Based Image Generation
661. ICML 2026ProRL: Effective Reinforcement Learning for Proactive Recommendation via Rectified Policy Gradient Estimation
662. ICML 2026Provable Benefits of RLVR over SFT for Reasoning Models: Learning to Backtrack Efficiently
663. ICML 2026Provable Sample Efficiency of Curriculum Post-Training for Transformer Reasoning
664. ICML 2026Provably Convergent Actor-Critic for MARL through Risk-aversion
665. ICML 2026Provably Efficient Policy-Reward Co-Pretraining for Adversarial Imitation Learning
666. ICML 2026PRPO: Paragraph-level Policy Optimization for Vision-Language Deepfake Detection
667. ICML 2026PS-PPO : Prefix-Sampling PPO for Critic-Free RLHF
668. ICML 2026Pushing Forward Pareto Frontiers of Proactive Agents with Behavioral Agentic Optimization
669. ICML 2026PyVision-RL: Forging Open Agentic Vision Models via RL
670. ICML 2026Q-Flow: Stable and Expressive Reinforcement Learning with Flow-based Policy
671. ICML 2026Q-SAM: Unlocking Sharpness-Aware Minimization for Generalization in Offline Reinforcement Learning
672. ICML 2026QHyer: Q-conditioned Hybrid Attention-mamba Transformer for Offline Goal-conditioned RL
673. ICML 2026Quantifying and Optimizing Simplicity via Polynomial Representations
674. ICML 2026Quantum Robust Inner Minimization for Reinforcement Learning with Quadratic Speed-Up in Query Complexity
675. ICML 2026QUATRO: Query-Adaptive Trust Region Policy Optimization for LLM Fine-tuning
676. ICML 2026R-Diverse: Mitigating Diversity Illusion in Self-Play LLM Training
677. ICML 2026R1-SyntheticVL: Is Synthetic Data from Generative Models Ready for Multimodal Large Language Model?
678. ICML 2026R2R2: Robust Representation for Intensive Experience Reuse via Redundancy Reduction in Self-Predictive Learning
679. ICML 2026RAD: Retrieval High-quality Demonstrations to Enhance Decision-making
680. ICML 2026RAGEN-2: Reasoning Collapse in Agentic RL
681. ICML 2026RAMAC: Multimodal Risk-Aware Offline Reinforcement Learning and the Role of Behavior Regularization
682. ICML 2026Randomized Advantage Transformation (RAT): Computing Natural Policy Gradients via Direct Backpropagation
683. ICML 2026RAST-MoE-RL: A Regime-Aware Spatio-Temporal MoE Framework for Deep Reinforcement Learning in Ride-Hailing
684. ICML 2026Rate or Fate? RLV$^{\varepsilon}$R: Reinforcement Learning with Verifiable Noisy Rewards
685. ICML 2026Ratio-Variance Regularized Policy Optimization
686. ICML 2026Rationality Measurement and Theory for Reinforcement Learning Agents
687. ICML 2026Real-Time Aligned Reward Model beyond Semantics
688. ICML 2026REAL: Regression-Aware Reinforcement Learning for LLM-as-a-Judge
689. ICML 2026Reasoning Cache: Continual Improvement Over Long Horizons via Short-Horizon RL
690. ICML 2026Reasoning-VLA: An Efficient and Spatial-Guided General Vision-Language-Action Reasoning Model for Autonomous Driving
691. ICML 2026ReAugment: Targeted Few-Shot Time Series Augmentation via Model Zoo-Guided Reinforcement Learning
692. ICML 2026Recontextualization Mitigates Specification Gaming Without Modifying the Specification
693. ICML 2026Recovering Hidden Reward in Diffusion-Based Policies
694. ICML 2026Recurrent Equivariant Constraint Modulation: Learning Per-Layer Symmetry Relaxation from Data
695. ICML 2026Recurrent Structural Policy Gradient for Partially Observable Mean Field Games
696. ICML 2026Refined Analysis of Entropy-Regularized Actor-Critic
697. ICML 2026Reflect-then-Correct: Rebalancing Task Optimization for Generalizable Meta-Reinforcement Learning via Distributional Value Error Reduction
698. ICML 2026Reflector: Internalizing Step-wise Reflection against Indirect Jailbreaks
699. ICML 2026REG: In-Sample RL via Regularizing the Evaluation Gap
700. ICML 2026Regularized Offline Policy Optimization with Posterior Hybrid Bayesian Belief

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.