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

2,079 papers, page 23 of 42

1101. ICML 2025Convergence of Policy Mirror Descent Beyond Compatible Function Approximation
1102. ICML 2025Convex Markov Games: A New Frontier for Multi-Agent Reinforcement Learning
1103. ICML 2025Counting atoms faster: policy-based nuclear magnetic resonance pulse sequencing for atomic abundance measurement
1104. ICML 2025Craftium: Bridging Flexibility and Efficiency for Rich 3D Single- and Multi-Agent Environments
1105. ICML 2025Cross-environment Cooperation Enables Zero-shot Multi-agent Coordination
1106. ICML 2025D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples
1107. ICML 2025David and Goliath: Small One-step Model Beats Large Diffusion with Score Post-training
1108. ICML 2025Decision Mixer: Integrating Long-term and Local Dependencies via Dynamic Token Selection for Decision-Making
1109. ICML 2025Decoding Rewards in Competitive Games: Inverse Game Theory with Entropy Regularization
1110. ICML 2025Deep Reinforcement Learning from Hierarchical Preference Design
1111. ICML 2025Demonstration Selection for In-Context Learning via Reinforcement Learning
1112. ICML 2025Demystifying Long Chain-of-Thought Reasoning
1113. ICML 2025Demystifying the Paradox of Importance Sampling with an Estimated History-Dependent Behavior Policy in Off-Policy Evaluation
1114. ICML 2025Design Considerations in Offline Preference-based RL
1115. ICML 2025DiLQR: Differentiable Iterative Linear Quadratic Regulator via Implicit Differentiation
1116. ICML 2025DiMa: Understanding the Hardness of Online Matching Problems via Diffusion Models
1117. ICML 2025DIME: Diffusion-Based Maximum Entropy Reinforcement Learning
1118. ICML 2025DipLLM: Fine-Tuning LLM for Strategic Decision-making in Diplomacy
1119. ICML 2025Directly Forecasting Belief for Reinforcement Learning with Delays
1120. ICML 2025Discriminative Policy Optimization for Token-Level Reward Models
1121. ICML 2025Distributionally Robust Multi-Agent Reinforcement Learning for Dynamic Chute Mapping
1122. ICML 2025Distributionally Robust Policy Learning under Concept Drifts
1123. ICML 2025Diversifying Robot Locomotion Behaviors with Extrinsic Behavioral Curiosity
1124. ICML 2025Diversity By Design: Leveraging Distribution Matching for Offline Model-Based Optimization
1125. ICML 2025Divide and Conquer: Grounding LLMs as Efficient Decision-Making Agents via Offline Hierarchical Reinforcement Learning
1126. ICML 2025Diving into Self-Evolving Training for Multimodal Reasoning
1127. ICML 2025Do We Need to Verify Step by Step? Rethinking Process Supervision from a Theoretical Perspective
1128. ICML 2025DPO Meets PPO: Reinforced Token Optimization for RLHF
1129. ICML 2025DSBRouter: End-to-end Global Routing via Diffusion Schr\"{o}dinger Bridge
1130. ICML 2025EARL-BO: Reinforcement Learning for Multi-Step Lookahead, High-Dimensional Bayesian Optimization
1131. ICML 2025Efficient Online Reinforcement Learning for Diffusion Policy
1132. ICML 2025Efficient Skill Discovery via Regret-Aware Optimization
1133. ICML 2025EGPlace: An Efficient Macro Placement Method via Evolutionary Search with Greedy Repositioning Guided Mutation
1134. ICML 2025ELEMENTAL: Interactive Learning from Demonstrations and Vision-Language Models for Reward Design in Robotics
1135. ICML 2025Eliciting Language Model Behaviors with Investigator Agents
1136. ICML 2025Embedding Safety into RL: A New Take on Trust Region Methods
1137. ICML 2025Empirical Design in Reinforcement Learning
1138. ICML 2025Enabling Optimal Decisions in Rehearsal Learning under CARE Condition
1139. ICML 2025Enhancing Cooperative Multi-Agent Reinforcement Learning with State Modelling and Adversarial Exploration
1140. ICML 2025Enhancing Decision-Making of Large Language Models via Actor-Critic
1141. ICML 2025Enhancing Diversity In Parallel Agents: A Maximum State Entropy Exploration Story
1142. ICML 2025Enhancing Rating-Based Reinforcement Learning to Effectively Leverage Feedback from Large Vision-Language Models
1143. ICML 2025Ergodic Generative Flows
1144. ICML 2025EvoControl: Multi-Frequency Bi-Level Control for High-Frequency Continuous Control
1145. ICML 2025EVOLvE: Evaluating and Optimizing LLMs For In-Context Exploration
1146. ICML 2025Exact Recovery of Sparse Binary Vectors from Generalized Linear Measurements
1147. ICML 2025Explainable Concept Generation through Vision-Language Preference Learning for Understanding Neural Networks' Internal Representations
1148. ICML 2025Explicit Exploration for High-Welfare Equilibria in Game-Theoretic Multiagent Reinforcement Learning
1149. ICML 2025Explicit Preference Optimization: No Need for an Implicit Reward Model
1150. ICML 2025Exploring Large Action Sets with Hyperspherical Embeddings using von Mises-Fisher Sampling

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.