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

6,885 papers, page 125 of 138

6201. ICML 2023Hierarchical Diffusion for Offline Decision Making
6202. ICML 2023Hierarchical Imitation Learning with Vector Quantized Models
6203. ICML 2023Hierarchical Programmatic Reinforcement Learning via Learning to Compose Programs
6204. ICML 2023Hierarchies of Reward Machines
6205. ICML 2023Hindsight Learning for MDPs with Exogenous Inputs
6206. ICML 2023Homomorphism AutoEncoder --- Learning Group Structured Representations from Observed Transitions
6207. ICML 2023Horizon-Free and Variance-Dependent Reinforcement Learning for Latent Markov Decision Processes
6208. ICML 2023Horizon-free Learning for Markov Decision Processes and Games: Stochastically Bounded Rewards and Improved Bounds
6209. ICML 2023Human-Timescale Adaptation in an Open-Ended Task Space
6210. ICML 2023Hyperparameters in Reinforcement Learning and How To Tune Them
6211. ICML 2023Identifiability and Generalizability in Constrained Inverse Reinforcement Learning
6212. ICML 2023Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation
6213. ICML 2023Improving Bi-level Optimization Based Methods with Inspiration from Humans' Classroom Study Techniques
6214. ICML 2023Individually Fair Learning with One-Sided Feedback
6215. ICML 2023Information-Theoretic State Space Model for Multi-View Reinforcement Learning
6216. ICML 2023Interactive Object Placement with Reinforcement Learning
6217. ICML 2023Internally Rewarded Reinforcement Learning
6218. ICML 2023Invariance in Policy Optimisation and Partial Identifiability in Reward Learning
6219. ICML 2023Inverse Reinforcement Learning without Reinforcement Learning
6220. ICML 2023Investigating the Role of Model-Based Learning in Exploration and Transfer
6221. ICML 2023Jump-Start Reinforcement Learning
6222. ICML 2023Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning
6223. ICML 2023Language Instructed Reinforcement Learning for Human-AI Coordination
6224. ICML 2023Lazy Agents: A New Perspective on Solving Sparse Reward Problem in Multi-agent Reinforcement Learning
6225. ICML 2023Learning Belief Representations for Partially Observable Deep RL
6226. ICML 2023Learning Compiler Pass Orders using Coreset and Normalized Value Prediction
6227. ICML 2023Learning Control-Oriented Dynamical Structure from Data
6228. ICML 2023Learning for Edge-Weighted Online Bipartite Matching with Robustness Guarantees
6229. ICML 2023Learning GFlowNets From Partial Episodes For Improved Convergence And Stability
6230. ICML 2023Learning in POMDPs is Sample-Efficient with Hindsight Observability
6231. ICML 2023Learning Neural Constitutive Laws from Motion Observations for Generalizable PDE Dynamics
6232. ICML 2023Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation
6233. ICML 2023Learning Signed Distance Functions from Noisy 3D Point Clouds via Noise to Noise Mapping
6234. ICML 2023Learning Temporally AbstractWorld Models without Online Experimentation
6235. ICML 2023Learning the Dynamics of Sparsely Observed Interacting Systems
6236. ICML 2023Learning to Design Analog Circuits to Meet Threshold Specifications
6237. ICML 2023Learning to Learn from APIs: Black-Box Data-Free Meta-Learning
6238. ICML 2023Learning to Maximize Mutual Information for Dynamic Feature Selection
6239. ICML 2023Learning to Optimize Differentiable Games
6240. ICML 2023Learning Unforeseen Robustness from Out-of-distribution Data Using Equivariant Domain Translator
6241. ICML 2023Learning useful representations for shifting tasks and distributions
6242. ICML 2023LESSON: Learning to Integrate Exploration Strategies for Reinforcement Learning via an Option Framework
6243. ICML 2023Leveraging Offline Data in Online Reinforcement Learning
6244. ICML 2023LinSATNet: The Positive Linear Satisfiability Neural Networks
6245. ICML 2023LipsNet: A Smooth and Robust Neural Network with Adaptive Lipschitz Constant for High Accuracy Optimal Control
6246. ICML 2023LIV: Language-Image Representations and Rewards for Robotic Control
6247. ICML 2023Live in the Moment: Learning Dynamics Model Adapted to Evolving Policy
6248. ICML 2023Local Optimization Achieves Global Optimality in Multi-Agent Reinforcement Learning
6249. ICML 2023Low-Switching Policy Gradient with Exploration via Online Sensitivity Sampling
6250. ICML 2023Lower Bounds for Learning in Revealing POMDPs

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.