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 3 of 42

101. ICML 2026Beyond Two-Stage Training: Cooperative SFT and RL for LLM Reasoning
102. ICML 2026Bias in Zeroth-Order Normal Estimation for Decision-Based Attacks
103. ICML 2026Bilevel Optimization over Saddle Points of Zero-Sum Markov Games
104. ICML 2026BIT-LLM: Brain Instruction Tuned LLM with persistent Cross-Attention for fMRI-to-Text Decoding
105. ICML 2026BiTrajDiff: Bidirectional Trajectory Generation with Diffusion Models for Offline Reinforcement Learning
106. ICML 2026Black-Box Combinatorial Optimization with Order-Invariant Reinforcement Learning
107. ICML 2026Blending Supervised and Reinforcement Fine-Tuning with Prefix Sampling
108. ICML 2026BOOSTAPR: Boosting Automated Program Repair via Execution-Grounded Reinforcement Learning with Dual Reward Models
109. ICML 2026Boosting CVaR Policy Optimization with Quantile Gradients
110. ICML 2026Boosting World Models Learning via Latent-Space Value Alignment
111. ICML 2026Bottleneck Communication Delay Minimization for Communication-Efficient Decentralized Learning
112. ICML 2026Bottleneck-Guided Spectral Subgoals For Offline Goal-Conditioned RL
113. ICML 2026Break the Block: Dynamic-size Reasoning Blocks for Diffusion Large Language Models via Monotonic Entropy Descent with Reinforcement Learning
114. ICML 2026Breaking Multi-Task Curse: Reward-Weighted Evolution for Black-Box Many-Task Optimization
115. ICML 2026Breaking the Computational Barrier: Provably Efficient Actor–Critic for Low-Rank MDPs
116. ICML 2026Breaking the Exploration Bottleneck: Rubric-Scaffolded Reinforcement Learning for Open-Ended LLM Reasoning
117. ICML 2026Breaking the Factorization Barrier in Diffusion Language Models
118. ICML 2026Breaking the Self-Confirming Loop: Diagnosing and Mitigating Systemic Reward Bias in Self-Rewarding RL
119. ICML 2026Bridging On-Device and Cloud LLMs for Collaborative Reasoning: A Unified Methodology for Local Routing and Post-Training
120. ICML 2026Bridging the Gap Between Average and Discounted TD Learning
121. ICML 2026Bringing Code ALIVE: Optimizing Interactive Frontend Mini-Games via Automated Play and Reinforcement Learning at Scale
122. ICML 2026BroRL: Scaling Reinforcement Learning via Broadened Exploration
123. ICML 2026BubbleSpec: Turning Long-Tail Bubbles into Speculative Rollout Drafts for Synchronous Reinforcement Learning
124. ICML 2026Budget-Efficient Attacks and Robustness Training for Cooperative MARL
125. ICML 2026CALM Before the STORM: Unlocking Native Reasoning for Optimization Modeling
126. ICML 2026CAMEL: Confidence-Gated Reflection for Reward Modeling
127. ICML 2026Can Agents Generalize to the Open World? Unveiling the Fragility of Static Training in Tool Use
128. ICML 2026Can Large Language Models Generalize Procedures Across Representations?
129. ICML 2026Can Vision Language Models Learn Intuitive Physics from Interaction?
130. ICML 2026CaP-X: A Framework for Benchmarking and Improving Coding Agents for Robot Manipulation
131. ICML 2026Causal Flow Q-Learning for Robust Offline Reinforcement Learning
132. ICML 2026CausalXRL: Explainable Reinforcement Learning through Causal Graph Reasoning
133. ICML 2026Cerebellar-Inspired Residual Control for Fault Recovery: From Inference-Time Adaptation to Structural Consolidation
134. ICML 2026CFPO: Counterfactual Policy Optimization for Multimodal Reasoning
135. ICML 2026Chain-of-Glimpse: Search-Guided Progressive Object-Grounded Reasoning for Video Understanding
136. ICML 2026Chain-of-Goals Hierarchical Policy for Long-Horizon Offline Goal-Conditioned RL
137. ICML 2026Chasing Moving Targets with Online Self-Play Reinforcement Learning for Safer Language Models
138. ICML 2026Chebyshev Policies and the Mountain Car Problem: Reinforcement Learning for Low-Dimensional Control Tasks
139. ICML 2026Chunk-Guided Q-Learning
140. ICML 2026Clipped Q-Learning: Your Value Clipping Is Secretly A Robust Operator
141. ICML 2026Clipping Bottleneck: Stabilizing RLVR via Stochastic Recovery of Near-Boundary Signals
142. ICML 2026Clipping Low-Probability Tokens in SFT Yields a Generalizable Initialization for RL
143. ICML 2026Closing the Sim-to-Real Gap in Non-Markovian Spreading Processes via GPU-Accelerated Distributional RL
144. ICML 2026Co-Evolving Latent Action World Models
145. ICML 2026CoCoEdit: Content-Consistent Image Editing via Region Regularized Reinforcement Learning
146. ICML 2026CocoRNA: Collective RNA Design with Cooperative Multi-agent Reinforcement Learning
147. ICML 2026CofactGVR: Counterfactual Intervention for Grounded Visual Reasoning
148. ICML 2026CoIRL-AD: Collaborative-Competitive Imitation-Reinforcement Learning in Latent World Models for Autonomous Driving
149. ICML 2026COLLIE: Guiding Skill Discovery in Semantically Coherent Latent Space
150. ICML 2026Commit to the Bit: Reactive Reinforcement Learning Done Right

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.