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

2,985 papers, page 19 of 60

901. ICLR 2026Reasoning-Aligned Perception Decoupling for Scalable Multi-modal Reasoning
902. ICLR 2026RECAST: Expanding the Boundaries of LLMs' Complex Instruction Following with Multi-Constraint Data
903. ICLR 2026ReCogDrive: A Reinforced Cognitive Framework for End-to-End Autonomous Driving
904. ICLR 2026Rectifying LLM Thought from Lens of Optimization
905. ICLR 2026Recurrent Action Transformer with Memory
906. ICLR 2026Reducing Belief Deviation in Reinforcement Learning for Active Reasoning
907. ICLR 2026Reevaluating Policy Gradient Methods for Imperfect-Information Games
908. ICLR 2026Reference Guided Skill Discovery
909. ICLR 2026References Improve LLM Alignment in Non-Verifiable Domains
910. ICLR 2026Refining Hybrid Genetic Search for CVRP via Reinforcement Learning-Finetuned LLM
911. ICLR 2026ReFORM: Reflected Flows for On-support Offline RL via Noise Manipulation
912. ICLR 2026RegionReasoner: Region-Grounded Multi-Round Visual Reasoning
913. ICLR 2026Regret-Guided Search Control for Efficient Learning in AlphaZero
914. ICLR 2026Regularized Latent Dynamics Prediction is a Strong Baseline For Behavioral Foundation Models
915. ICLR 2026Reinforced Latent Reasoning for LLM-based Recommendation
916. ICLR 2026Reinforcement Learning Fine-Tuning Enhances Activation Intensity and Diversity in the Internal Circuitry of LLMs
917. ICLR 2026Reinforcement Learning for Machine Learning Engineering Agents
918. ICLR 2026Reinforcement Learning from Dynamic Critic Feedback for Free-Form Generations
919. ICLR 2026Reinforcement Learning with Verifiable Rewards Implicitly Incentivizes Correct Reasoning in Base LLMs
920. ICLR 2026Reinforcement Mid-Training
921. ICLR 2026Reinforcement Unlearning via Group Relative Policy Optimization
922. ICLR 2026Reinforcing Diffusion Models by Direct Group Preference Optimization
923. ICLR 2026Reinforcing General Reasoning Without Verifiers
924. ICLR 2026Relative Entropy Pathwise Policy Optimization
925. ICLR 2026Relative Value Learning
926. ICLR 2026Reliability-Adjusted Prioritized Experience Replay
927. ICLR 2026Replicable Reinforcement Learning with Linear Function Approximation
928. ICLR 2026Representation-Based Exploration for Language Models: From Test-Time to Post-Training
929. ICLR 2026RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning
930. ICLR 2026RESCHED: Rethinking Flexible Job Shop Scheduling from a Transformer-based Architecture with Simplified States
931. ICLR 2026Reshaping Reasoning in LLMs: A Theoretical Analysis of RL Training Dynamics through Pattern Selection
932. ICLR 2026Resisting Contextual Interference in RAG via Parametric-Knowledge Reinforcement
933. ICLR 2026ResT: Reshaping Token-Level Policy Gradients for Tool-Use Large Language Models
934. ICLR 2026RESTRAIN: From Spurious Votes to Signals — Self-Training RL with Self-Penalization
935. ICLR 2026Retaining Suboptimal Actions to Follow Shifting Optima in Multi-Agent Reinforcement Learning
936. ICLR 2026Rethinking Policy Diversity in Ensemble Policy Gradient in Large-Scale Reinforcement Learning
937. ICLR 2026ReTool: Reinforcement Learning for Strategic Tool Use in LLMs
938. ICLR 2026ReTrace: Reinforcement Learning-Guided Reconstruction Attacks on Machine Unlearning
939. ICLR 2026Retro*: Optimizing LLMs for Reasoning-Intensive Document Retrieval
940. ICLR 2026ReVeal: Self-Evolving Code Agents via Reliable Self-Verification
941. ICLR 2026Reverse-Engineered Reasoning for Open-Ended Generation
942. ICLR 2026Revisiting Group Relative Policy Optimization: Insights into On-Policy and Off-Policy Training
943. ICLR 2026Revisual-R1: Advancing Multimodal Reasoning From Optimized Cold Start to Staged Reinforcement Learning
944. ICLR 2026Revolutionizing Reinforcement Learning Framework for Diffusion Large Language Models
945. ICLR 2026Reward Is Enough: LLMs Are In-Context Reinforcement Learners
946. ICLR 2026Reward Model Routing in Alignment
947. ICLR 2026RewardEval: Advancing Reward Model Evaluation
948. ICLR 2026Rewarding Doubt: A Reinforcement Learning Approach to Calibrated Confidence Expression of Large Language Models
949. ICLR 2026RewardMap: Tackling Sparse Rewards in Fine-grained Visual Reasoning via Multi-Stage Reinforcement Learning
950. ICLR 2026RFS: Reinforcement learning with Residual flow steering for dexterous manipulation

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.