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

466 papers, page 6 of 10

251. NeurIPS 2024MiSO: Optimizing brain stimulation to create neural activity states
252. NeurIPS 2024Mitigating Covariate Shift in Behavioral Cloning via Robust Stationary Distribution Correction
253. NeurIPS 2024Mitigating Partial Observability in Sequential Decision Processes via the Lambda Discrepancy
254. NeurIPS 2024Mitigating Reward Overoptimization via Lightweight Uncertainty Estimation
255. NeurIPS 2024Model-based Diffusion for Trajectory Optimization
256. NeurIPS 2024Model-Based Transfer Learning for Contextual Reinforcement Learning
257. NeurIPS 2024Model-free Low-Rank Reinforcement Learning via Leveraged Entry-wise Matrix Estimation
258. NeurIPS 2024MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-Training
259. NeurIPS 2024Multi-Agent Coordination via Multi-Level Communication
260. NeurIPS 2024Multi-Agent Domain Calibration with a Handful of Offline Data
261. NeurIPS 2024Multi-Agent Imitation Learning: Value is Easy, Regret is Hard
262. NeurIPS 2024Multi-Reward Best Policy Identification
263. NeurIPS 2024Multi-turn Reinforcement Learning with Preference Human Feedback
264. NeurIPS 2024Multimodal Large Language Models Make Text-to-Image Generative Models Align Better
265. NeurIPS 2024Mutli-Armed Bandits with Network Interference
266. NeurIPS 2024N-agent Ad Hoc Teamwork
267. NeurIPS 2024Near-Minimax-Optimal Distributional Reinforcement Learning with a Generative Model
268. NeurIPS 2024Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms
269. NeurIPS 2024Near-Optimal Dynamic Regret for Adversarial Linear Mixture MDPs
270. NeurIPS 2024NeoRL: Efficient Exploration for Nonepisodic RL
271. NeurIPS 2024NetworkGym: Reinforcement Learning Environments for Multi-Access Traffic Management in Network Simulation
272. NeurIPS 2024Neural Combinatorial Optimization for Robust Routing Problem with Uncertain Travel Times
273. NeurIPS 2024NeuralPlane: An Efficiently Parallelizable Platform for Fixed-wing Aircraft Control with Reinforcement Learning
274. NeurIPS 2024No Regrets: Investigating and Improving Regret Approximations for Curriculum Discovery
275. NeurIPS 2024No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO
276. NeurIPS 2024Noise Contrastive Alignment of Language Models with Explicit Rewards
277. NeurIPS 2024Non-asymptotic Analysis of Biased Adaptive Stochastic Approximation
278. NeurIPS 2024Non-Stationary Learning of Neural Networks with Automatic Soft Parameter Reset
279. NeurIPS 2024Normalization and effective learning rates in reinforcement learning
280. NeurIPS 2024OASIS: Conditional Distribution Shaping for Offline Safe Reinforcement Learning
281. NeurIPS 2024Occupancy-based Policy Gradient: Estimation, Convergence, and Optimality
282. NeurIPS 2024ODRL: A Benchmark for Off-Dynamics Reinforcement Learning
283. NeurIPS 2024Off-Dynamics Reinforcement Learning via Domain Adaptation and Reward Augmented Imitation
284. NeurIPS 2024Off-policy estimation with adaptively collected data: the power of online learning
285. NeurIPS 2024Off-Policy Selection for Initiating Human-Centric Experimental Design
286. NeurIPS 2024Offline Behavior Distillation
287. NeurIPS 2024Offline Multitask Representation Learning for Reinforcement Learning
288. NeurIPS 2024Offline Oracle-Efficient Learning for Contextual MDPs via Layerwise Exploration-Exploitation Tradeoff
289. NeurIPS 2024Offline Reinforcement Learning with OOD State Correction and OOD Action Suppression
290. NeurIPS 2024OmniJARVIS: Unified Vision-Language-Action Tokenization Enables Open-World Instruction Following Agents
291. NeurIPS 2024On the Complexity of Teaching a Family of Linear Behavior Cloning Learners
292. NeurIPS 2024On the Curses of Future and History in Future-dependent Value Functions for Off-policy Evaluation
293. NeurIPS 2024On the Role of Information Structure in Reinforcement Learning for Partially-Observable Sequential Teams and Games
294. NeurIPS 2024One-Shot Safety Alignment for Large Language Models via Optimal Dualization
295. NeurIPS 2024Online Control with Adversarial Disturbance for Continuous-time Linear Systems
296. NeurIPS 2024Online Iterative Reinforcement Learning from Human Feedback with General Preference Model
297. NeurIPS 2024OPERA: Automatic Offline Policy Evaluation with Re-weighted Aggregates of Multiple Estimators
298. NeurIPS 2024Operator World Models for Reinforcement Learning
299. NeurIPS 2024Opponent Modeling based on Subgoal Inference
300. NeurIPS 2024Opponent Modeling with In-context Search

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.