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

1,640 papers, page 22 of 33

1051. NeurIPS 2025Enhancing the Outcome Reward-based RL Training of MLLMs with Self-Consistency Sampling
1052. NeurIPS 2025Enigmata: Scaling Logical Reasoning in Large Language Models with Synthetic Verifiable Puzzles
1053. NeurIPS 2025Equilibrium Policy Generalization: A Reinforcement Learning Framework for Cross-Graph Zero-Shot Generalization in Pursuit-Evasion Games
1054. NeurIPS 2025ESCORT: Efficient Stein-variational and Sliced Consistency-Optimized Temporal Belief Representation for POMDPs
1055. NeurIPS 2025Estimating cognitive biases with attention-aware inverse planning
1056. NeurIPS 2025EVAAA: A Virtual Environment Platform for Essential Variables in Autonomous and Adaptive Agents
1057. NeurIPS 2025EvoLM: In Search of Lost Language Model Training Dynamics
1058. NeurIPS 2025EvolvedGRPO: Unlocking Reasoning in LVLMs via Progressive Instruction Evolution
1059. NeurIPS 2025Explainable Reinforcement Learning from Human Feedback to Improve Alignment
1060. NeurIPS 2025Explainably Safe Reinforcement Learning
1061. NeurIPS 2025Exploration from a Primal-Dual Lens: Value-Incentivized Actor-Critic Methods for Sample-Efficient Online RL
1062. NeurIPS 2025Exploring Data Scaling Trends and Effects in Reinforcement Learning from Human Feedback
1063. NeurIPS 2025ExPO: Unlocking Hard Reasoning with Self-Explanation-Guided Reinforcement Learning
1064. NeurIPS 2025Fact-R1: Towards Explainable Video Misinformation Detection with Deep Reasoning
1065. NeurIPS 2025Failure Prediction at Runtime for Generative Robot Policies
1066. NeurIPS 2025Fair Cooperation in Mixed-Motive Games via Conflict-Aware Gradient Adjustment
1067. NeurIPS 2025FairDICE: Fairness-Driven Offline Multi-Objective Reinforcement Learning
1068. NeurIPS 2025Faithful Dynamic Imitation Learning from Human Intervention with Dynamic Regret Minimization
1069. NeurIPS 2025FANS: A Flatness-Aware Network Structure for Generalization in Offline Reinforcement Learning
1070. NeurIPS 2025Fast exact recovery of noisy matrix from few entries: the infinity norm approach
1071. NeurIPS 2025Fast Monte Carlo Tree Diffusion: 100× Speedup via Parallel and Sparse Planning
1072. NeurIPS 2025Fast-Slow Thinking GRPO for Large Vision-Language Model Reasoning
1073. NeurIPS 2025Faster Fixed-Point Methods for Multichain MDPs
1074. NeurIPS 2025Federated Multi-armed Bandits with Efficient Bit-Level Communications
1075. NeurIPS 2025Fine-grained List-wise Alignment for Generative Medication Recommendation
1076. NeurIPS 2025Fine-Tuning Discrete Diffusion Models with Policy Gradient Methods
1077. NeurIPS 2025FineRS: Fine-grained Reasoning and Segmentation of Small Objects with Reinforcement Learning
1078. NeurIPS 2025Finite Sample Analysis of Linear Temporal Difference Learning with Arbitrary Features
1079. NeurIPS 2025Finite-Sample Analysis of Policy Evaluation for Robust Average Reward Reinforcement Learning
1080. NeurIPS 2025Finite-Time Bounds for Average-Reward Fitted Q-Iteration
1081. NeurIPS 2025First SFT, Second RL, Third UPT: Continual Improving Multi-Modal LLM Reasoning via Unsupervised Post-Training
1082. NeurIPS 2025Flattening Hierarchies with Policy Bootstrapping
1083. NeurIPS 2025Flow Matching-Based Autonomous Driving Planning with Advanced Interactive Behavior Modeling
1084. NeurIPS 2025Flow-Based Policy for Online Reinforcement Learning
1085. NeurIPS 2025Flow-GRPO: Training Flow Matching Models via Online RL
1086. NeurIPS 2025Focus-Then-Reuse: Fast Adaptation in Visual Perturbation Environments
1087. NeurIPS 2025Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models
1088. NeurIPS 2025ForceVLA: Enhancing VLA Models with a Force-aware MoE for Contact-rich Manipulation
1089. NeurIPS 2025Forecasting in Offline Reinforcement Learning for Non-stationary Environments
1090. NeurIPS 2025From Experts to a Generalist: Toward General Whole-Body Control for Humanoid Robots
1091. NeurIPS 2025From Kolmogorov to Cauchy: Shallow XNet Surpasses KANs
1092. NeurIPS 2025From Shortcut to Induction Head: How Data Diversity Shapes Algorithm Selection in Transformers
1093. NeurIPS 2025FUDOKI: Discrete Flow-based Unified Understanding and Generation via Kinetic-Optimal Velocities
1094. NeurIPS 2025Fuz-RL: A Fuzzy-Guided Robust Framework for Safe Reinforcement Learning under Uncertainty
1095. NeurIPS 2025General-Reasoner: Advancing LLM Reasoning Across All Domains
1096. NeurIPS 2025Generalizable Domain Adaptation for Sim-and-Real Policy Co-Training
1097. NeurIPS 2025Generalizing Experience for Language Agents with Hierarchical MetaFlows
1098. NeurIPS 2025Generalizing Verifiable Instruction Following
1099. NeurIPS 2025Generative RLHF-V: Learning Principles from Multi-modal Human Preference
1100. NeurIPS 2025Generative Trajectory Stitching through Diffusion Composition

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.