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 26 of 42

1251. ICML 2025NBDI: A Simple and Effective Termination Condition for Skill Extraction from Task-Agnostic Demonstrations
1252. ICML 2025Near-optimal Regret Using Policy Optimization in Online MDPs with Aggregate Bandit Feedback
1253. ICML 2025Near-Optimal Sample Complexity for MDPs via Anchoring
1254. ICML 2025Network Sparsity Unlocks the Scaling Potential of Deep Reinforcement Learning
1255. ICML 2025Neurosymbolic World Models for Sequential Decision Making
1256. ICML 2025Novelty Detection in Reinforcement Learning with World Models
1257. ICML 2025O-MAPL: Offline Multi-agent Preference Learning
1258. ICML 2025Of Mice and Machines: A Comparison of Learning Between Real World Mice and RL Agents
1259. ICML 2025Off-Policy Actor-Critic for Adversarial Observation Robustness: Virtual Alternative Training via Symmetric Policy Evaluation
1260. ICML 2025Off-Policy Evaluation under Nonignorable Missing Data
1261. ICML 2025Offline Opponent Modeling with Truncated Q-driven Instant Policy Refinement
1262. ICML 2025Offline-to-Online Reinforcement Learning with Classifier-Free Diffusion Generation
1263. ICML 2025Omni-Angle Assault: An Invisible and Powerful Physical Adversarial Attack on Face Recognition
1264. ICML 2025On Teacher Hacking in Language Model Distillation
1265. ICML 2025On the Adversarial Robustness of Multi-Kernel Clustering
1266. ICML 2025On the Guidance of Flow Matching
1267. ICML 2025On the Robustness of Reward Models for Language Model Alignment
1268. ICML 2025Online Episodic Convex Reinforcement Learning
1269. ICML 2025Online Laplacian-Based Representation Learning in Reinforcement Learning
1270. ICML 2025Online Learning in Risk Sensitive constrained MDP
1271. ICML 2025Online Pre-Training for Offline-to-Online Reinforcement Learning
1272. ICML 2025Online Robust Reinforcement Learning Through Monte-Carlo Planning
1273. ICML 2025Optimizing Language Models for Inference Time Objectives using Reinforcement Learning
1274. ICML 2025Optimizing Test-Time Compute via Meta Reinforcement Finetuning
1275. ICML 2025Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models
1276. ICML 2025Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization
1277. ICML 2025Partially Observable Reinforcement Learning with Memory Traces
1278. ICML 2025Penalizing Infeasible Actions and Reward Scaling in Reinforcement Learning with Offline Data
1279. ICML 2025Pessimism Principle Can Be Effective: Towards a Framework for Zero-Shot Transfer Reinforcement Learning
1280. ICML 2025PIGDreamer: Privileged Information Guided World Models for Safe Partially Observable Reinforcement Learning
1281. ICML 2025PILAF: Optimal Human Preference Sampling for Reward Modeling
1282. ICML 2025PIPA: Preference Alignment as Prior-Informed Statistical Estimation
1283. ICML 2025Policy Filtration for RLHF to Mitigate Noise in Reward Models
1284. ICML 2025Policy Gradient with Tree Expansion
1285. ICML 2025Policy Guided Tree Search for Enhanced LLM Reasoning
1286. ICML 2025Policy Optimization for CMDPs with Bandit Feedback: Learning Stochastic and Adversarial Constraints
1287. ICML 2025Policy Regularization on Globally Accessible States in Cross-Dynamics Reinforcement Learning
1288. ICML 2025Policy-labeled Preference Learning: Is Preference Enough for RLHF?
1289. ICML 2025Policy-Regret Minimization in Markov Games with Function Approximation
1290. ICML 2025Polynomial-Time Approximability of Constrained Reinforcement Learning
1291. ICML 2025Position: Constants are Critical in Regret Bounds for Reinforcement Learning
1292. ICML 2025Position: General Intelligence Requires Reward-based Pretraining
1293. ICML 2025Position: Iterative Online-Offline Joint Optimization is Needed to Manage Complex LLM Copyright Risks
1294. ICML 2025Position: Lifetime tuning is incompatible with continual reinforcement learning
1295. ICML 2025Position: LLMs Need a Bayesian Meta-Reasoning Framework for More Robust and Generalizable Reasoning
1296. ICML 2025Position: We Need An Algorithmic Understanding of Generative AI
1297. ICML 2025Power Mean Estimation in Stochastic Continuous Monte-Carlo Tree Search
1298. ICML 2025Preference Adaptive and Sequential Text-to-Image Generation
1299. ICML 2025Preference Controllable Reinforcement Learning with Advanced Multi-Objective Optimization
1300. ICML 2025Preference Optimization for Combinatorial Optimization Problems

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.