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 23 of 33

1101. NeurIPS 2025Generator-Mediated Bandits: Thompson Sampling for GenAI-Powered Adaptive Interventions
1102. NeurIPS 2025GenPO: Generative Diffusion Models Meet On-Policy Reinforcement Learning
1103. NeurIPS 2025GLID$^2$E: A Gradient-Free Lightweight Fine-tune Approach for Discrete Biological Sequence Design
1104. NeurIPS 2025Global Convergence for Average Reward Constrained MDPs with Primal-Dual Actor Critic Algorithm
1105. NeurIPS 2025Globally Optimal Policy Gradient Algorithms for Reinforcement Learning with PID Control Policies
1106. NeurIPS 2025GoalLadder: Incremental Goal Discovery with Vision-Language Models
1107. NeurIPS 2025GPO: Learning from Critical Steps to Improve LLM Reasoning
1108. NeurIPS 2025Graph Neural Network Based Action Ranking for Planning
1109. NeurIPS 2025GraphChain: Large Language Models for Large-scale Graph Analysis via Tool Chaining
1110. NeurIPS 2025Greedy Sampling Is Provably Efficient For RLHF
1111. NeurIPS 2025GRIT: Teaching MLLMs to Think with Images
1112. NeurIPS 2025Ground-Compose-Reinforce: Grounding Language in Agentic Behaviours using Limited Data
1113. NeurIPS 2025Grounded Reinforcement Learning for Visual Reasoning
1114. NeurIPS 2025Group-in-Group Policy Optimization for LLM Agent Training
1115. NeurIPS 2025GuardReasoner-VL: Safeguarding VLMs via Reinforced Reasoning
1116. NeurIPS 2025GUI Exploration Lab: Enhancing Screen Navigation in Agents via Multi-Turn Reinforcement Learning
1117. NeurIPS 2025GUI-G1: Understanding R1-Zero-Like Training for Visual Grounding in GUI Agents
1118. NeurIPS 2025GUI-Rise: Structured Reasoning and History Summarization for GUI Navigation
1119. NeurIPS 2025Guiding Cross-Modal Representations with MLLM Priors via Preference Alignment
1120. NeurIPS 2025GVPO: Group Variance Policy Optimization for Large Language Model Post-Training
1121. NeurIPS 2025Gymnasium: A Standard Interface for Reinforcement Learning Environments
1122. NeurIPS 2025Hadamax Encoding: Elevating Performance in Model-Free Atari
1123. NeurIPS 2025HCRMP: An LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving
1124. NeurIPS 2025HelpSteer3-Preference: Open Human-Annotated Preference Data across Diverse Tasks and Languages
1125. NeurIPS 2025Hephaestus: Mixture Generative Modeling with Energy Guidance for Large-scale QoS Degradation
1126. NeurIPS 2025Heterogeneous Graph Transformers for Simultaneous Mobile Multi-Robot Task Allocation and Scheduling under Temporal Constraints
1127. NeurIPS 2025Hierarchical Optimization via LLM-Guided Objective Evolution for Mobility-on-Demand Systems
1128. NeurIPS 2025Hierarchical Semantic-Augmented Navigation: Optimal Transport and Graph-Driven Reasoning for Vision-Language Navigation
1129. NeurIPS 2025High-Dimensional Calibration from Swap Regret
1130. NeurIPS 2025High-order Interactions Modeling for Interpretable Multi-Agent Q-Learning
1131. NeurIPS 2025HMARL-CBF – Hierarchical Multi-Agent Reinforcement Learning with Control Barrier Functions for Safety-Critical Autonomous Systems
1132. NeurIPS 2025Horizon Reduction Makes RL Scalable
1133. NeurIPS 2025How Ensembles of Distilled Policies Improve Generalisation in Reinforcement Learning
1134. NeurIPS 2025How Far Are We from Optimal Reasoning Efficiency?
1135. NeurIPS 2025How to Train Your LLM Web Agent: A Statistical Diagnosis
1136. NeurIPS 2025Human-assisted Robotic Policy Refinement via Action Preference Optimization
1137. NeurIPS 2025Hybrid Latent Reasoning via Reinforcement Learning
1138. NeurIPS 2025HyperMARL: Adaptive Hypernetworks for Multi-Agent RL
1139. NeurIPS 2025Hyperphantasia: A Benchmark for Evaluating the Mental Visualization Capabilities of Multimodal LLMs
1140. NeurIPS 2025HYPRL: Reinforcement Learning of Control Policies for Hyperproperties
1141. NeurIPS 2025Imagine Beyond ! Distributionally Robust Autoencoding for State Space Coverage in Online Reinforcement Learning
1142. NeurIPS 2025Imagined Autocurricula
1143. NeurIPS 2025Imitation Beyond Expectation Using Pluralistic Stochastic Dominance
1144. NeurIPS 2025Imitation Learning with Temporal Logic Constraints
1145. NeurIPS 2025Implicit Reward as the Bridge: A Unified View of SFT and DPO Connections
1146. NeurIPS 2025Improving Data Efficiency for LLM Reinforcement Fine-tuning Through Difficulty-targeted Online Data Selection and Rollout Replay
1147. NeurIPS 2025Improving LLM General Preference Alignment via Optimistic Online Mirror Descent
1148. NeurIPS 2025Improving Model-Based Reinforcement Learning by Converging to Flatter Minima
1149. NeurIPS 2025Improving Monte Carlo Tree Search for Symbolic Regression
1150. NeurIPS 2025Improving planning and MBRL with temporally-extended actions

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.