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

304 papers, page 3 of 7

101. ICLR 2024Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations
102. ICLR 2024Goodhart's Law in Reinforcement Learning
103. ICLR 2024GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher
104. ICLR 2024H-GAP: Humanoid Control with a Generalist Planner
105. ICLR 2024Harnessing Density Ratios for Online Reinforcement Learning
106. ICLR 2024HAZARD Challenge: Embodied Decision Making in Dynamically Changing Environments
107. ICLR 2024Hindsight PRIORs for Reward Learning from Human Preferences
108. ICLR 2024Horizon-Free Regret for Linear Markov Decision Processes
109. ICLR 2024Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs
110. ICLR 2024Hybrid Internal Model: Learning Agile Legged Locomotion with Simulated Robot Response
111. ICLR 2024Identifying Policy Gradient Subspaces
112. ICLR 2024Illusory Attacks: Information-theoretic detectability matters in adversarial attacks
113. ICLR 2024Imitation Learning from Observation with Automatic Discount Scheduling
114. ICLR 2024Impact of Computation in Integral Reinforcement Learning for Continuous-Time Control
115. ICLR 2024Improved Efficiency Based on Learned Saccade and Continuous Scene Reconstruction From Foveated Visual Sampling
116. ICLR 2024Improving Generalization of Alignment with Human Preferences through Group Invariant Learning
117. ICLR 2024Improving Intrinsic Exploration by Creating Stationary Objectives
118. ICLR 2024Improving Offline RL by Blending Heuristics
119. ICLR 2024In-context Exploration-Exploitation for Reinforcement Learning
120. ICLR 2024Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions
121. ICLR 2024Integrating Planning and Deep Reinforcement Learning via Automatic Induction of Task Substructures
122. ICLR 2024Intelligent Switching for Reset-Free RL
123. ICLR 2024Interpretable Meta-Learning of Physical Systems
124. ICLR 2024Jumanji: a Diverse Suite of Scalable Reinforcement Learning Environments in JAX
125. ICLR 2024Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies
126. ICLR 2024L2P-MIP: Learning to Presolve for Mixed Integer Programming
127. ICLR 2024Language Control Diffusion: Efficiently Scaling through Space, Time, and Tasks
128. ICLR 2024Language Model Detectors Are Easily Optimized Against
129. ICLR 2024Language Model Self-improvement by Reinforcement Learning Contemplation
130. ICLR 2024Large Language Models as Generalizable Policies for Embodied Tasks
131. ICLR 2024Learning Decentralized Partially Observable Mean Field Control for Artificial Collective Behavior
132. ICLR 2024Learning Energy Decompositions for Partial Inference in GFlowNets
133. ICLR 2024Learning from Sparse Offline Datasets via Conservative Density Estimation
134. ICLR 2024Learning Hierarchical World Models with Adaptive Temporal Abstractions from Discrete Latent Dynamics
135. ICLR 2024Learning Interactive Real-World Simulators
136. ICLR 2024Learning Mean Field Games on Sparse Graphs: A Hybrid Graphex Approach
137. ICLR 2024Learning Multi-Agent Communication from Graph Modeling Perspective
138. ICLR 2024Learning Multi-Agent Communication with Contrastive Learning
139. ICLR 2024Learning Nash Equilibria in Rank-1 Games
140. ICLR 2024Learning to Act from Actionless Videos through Dense Correspondences
141. ICLR 2024Learning to Act without Actions
142. ICLR 2024Learning to Make Adherence-aware Advice
143. ICLR 2024Leftover Lunch: Advantage-based Offline Reinforcement Learning for Language Models
144. ICLR 2024Less or More From Teacher: Exploiting Trilateral Geometry For Knowledge Distillation
145. ICLR 2024Local Search GFlowNets
146. ICLR 2024Locality Sensitive Sparse Encoding for Learning World Models Online
147. ICLR 2024LOQA: Learning with Opponent Q-Learning Awareness
148. ICLR 2024Making RL with Preference-based Feedback Efficient via Randomization
149. ICLR 2024MAMBA: an Effective World Model Approach for Meta-Reinforcement Learning
150. ICLR 2024Massively Scalable Inverse Reinforcement Learning in Google Maps

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.