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

1,070 papers, page 21 of 22

1001. NeurIPS 2023Spatially Resolved Gene Expression Prediction from Histology Images via Bi-modal Contrastive Learning
1002. NeurIPS 2023Spectral Entry-wise Matrix Estimation for Low-Rank Reinforcement Learning
1003. NeurIPS 2023SPQR: Controlling Q-ensemble Independence with Spiked Random Model for Reinforcement Learning
1004. NeurIPS 2023SPRING: Studying Papers and Reasoning to play Games
1005. NeurIPS 2023State Regularized Policy Optimization on Data with Dynamics Shift
1006. NeurIPS 2023State Sequences Prediction via Fourier Transform for Representation Learning
1007. NeurIPS 2023State-Action Similarity-Based Representations for Off-Policy Evaluation
1008. NeurIPS 2023State2Explanation: Concept-Based Explanations to Benefit Agent Learning and User Understanding
1009. NeurIPS 2023StateMask: Explaining Deep Reinforcement Learning through State Mask
1010. NeurIPS 2023STEVE-1: A Generative Model for Text-to-Behavior in Minecraft
1011. NeurIPS 2023Stochastic Approximation Approaches to Group Distributionally Robust Optimization
1012. NeurIPS 2023STORM: Efficient Stochastic Transformer based World Models for Reinforcement Learning
1013. NeurIPS 2023Strategic Apple Tasting
1014. NeurIPS 2023Structured State Space Models for In-Context Reinforcement Learning
1015. NeurIPS 2023Successor-Predecessor Intrinsic Exploration
1016. NeurIPS 2023Suggesting Variable Order for Cylindrical Algebraic Decomposition via Reinforcement Learning
1017. NeurIPS 2023Supervised Pretraining Can Learn In-Context Reinforcement Learning
1018. NeurIPS 2023Supported Value Regularization for Offline Reinforcement Learning
1019. NeurIPS 2023Survival Instinct in Offline Reinforcement Learning
1020. NeurIPS 2023SustainGym: Reinforcement Learning Environments for Sustainable Energy Systems
1021. NeurIPS 2023Swarm Reinforcement Learning for Adaptive Mesh Refinement
1022. NeurIPS 2023Synthetic Experience Replay
1023. NeurIPS 2023T2T: From Distribution Learning in Training to Gradient Search in Testing for Combinatorial Optimization
1024. NeurIPS 2023Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds
1025. NeurIPS 2023Task-aware world model learning with meta weighting via bi-level optimization
1026. NeurIPS 2023TaskMet: Task-driven Metric Learning for Model Learning
1027. NeurIPS 2023Taylor TD-learning
1028. NeurIPS 2023TD Convergence: An Optimization Perspective
1029. NeurIPS 2023Team-PSRO for Learning Approximate TMECor in Large Team Games via Cooperative Reinforcement Learning
1030. NeurIPS 2023Tempo Adaptation in Non-stationary Reinforcement Learning
1031. NeurIPS 2023The Benefits of Being Distributional: Small-Loss Bounds for Reinforcement Learning
1032. NeurIPS 2023The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model
1033. NeurIPS 2023The Geometry of Neural Nets' Parameter Spaces Under Reparametrization
1034. NeurIPS 2023Thinker: Learning to Plan and Act
1035. NeurIPS 2023Thought Cloning: Learning to Think while Acting by Imitating Human Thinking
1036. NeurIPS 2023Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics
1037. NeurIPS 2023Towards robust and generalizable representations of extracellular data using contrastive learning
1038. NeurIPS 2023TradeMaster: A Holistic Quantitative Trading Platform Empowered by Reinforcement Learning
1039. NeurIPS 2023Train Hard, Fight Easy: Robust Meta Reinforcement Learning
1040. NeurIPS 2023Train Once, Get a Family: State-Adaptive Balances for Offline-to-Online Reinforcement Learning
1041. NeurIPS 2023Training Transitive and Commutative Multimodal Transformers with LoReTTa
1042. NeurIPS 2023Transportability for Bandits with Data from Different Environments
1043. NeurIPS 2023Truncating Trajectories in Monte Carlo Policy Evaluation: an Adaptive Approach
1044. NeurIPS 2023Trust Region-Based Safe Distributional Reinforcement Learning for Multiple Constraints
1045. NeurIPS 2023Two Heads are Better Than One: A Simple Exploration Framework for Efficient Multi-Agent Reinforcement Learning
1046. NeurIPS 2023Uncertainty Estimation for Safety-critical Scene Segmentation via Fine-grained Reward Maximization
1047. NeurIPS 2023Uncertainty-Aware Instance Reweighting for Off-Policy Learning
1048. NeurIPS 2023Understanding and Addressing the Pitfalls of Bisimulation-based Representations in Offline Reinforcement Learning
1049. NeurIPS 2023Understanding Contrastive Learning via Distributionally Robust Optimization
1050. NeurIPS 2023Understanding, Predicting and Better Resolving Q-Value Divergence in Offline-RL

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.