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

1,190 papers, page 7 of 24

301. ICLR 2024Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks
302. ICLR 2024Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent Adaptivity
303. ICLR 2024Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation
304. ICLR 2024Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight
305. ICLR 2024Sample-Efficient Multi-Agent RL: An Optimization Perspective
306. ICLR 2024Sample-Efficient Quality-Diversity by Cooperative Coevolution
307. ICLR 2024Score Models for Offline Goal-Conditioned Reinforcement Learning
308. ICLR 2024Score Regularized Policy Optimization through Diffusion Behavior
309. ICLR 2024SEABO: A Simple Search-Based Method for Offline Imitation Learning
310. ICLR 2024Searching for High-Value Molecules Using Reinforcement Learning and Transformers
311. ICLR 2024Selective Visual Representations Improve Convergence and Generalization for Embodied AI
312. ICLR 2024Simple Hierarchical Planning with Diffusion
313. ICLR 2024Skill Machines: Temporal Logic Skill Composition in Reinforcement Learning
314. ICLR 2024Skill or Luck? Return Decomposition via Advantage Functions
315. ICLR 2024Soft Robust MDPs and Risk-Sensitive MDPs: Equivalence, Policy Gradient, and Sample Complexity
316. ICLR 2024Solving Homogeneous and Heterogeneous Cooperative Tasks with Greedy Sequential Execution
317. ICLR 2024Spatially-Aware Transformers for Embodied Agents
318. ICLR 2024SRL: Scaling Distributed Reinforcement Learning to Over Ten Thousand Cores
319. ICLR 2024Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data
320. ICLR 2024STARC: A General Framework For Quantifying Differences Between Reward Functions
321. ICLR 2024Statistical Rejection Sampling Improves Preference Optimization
322. ICLR 2024Stylized Offline Reinforcement Learning: Extracting Diverse High-Quality Behaviors from Heterogeneous Datasets
323. ICLR 2024Submodular Reinforcement Learning
324. ICLR 2024SYMBOL: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning
325. ICLR 2024Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning
326. ICLR 2024Task Planning for Visual Room Rearrangement under Partial Observability
327. ICLR 2024TD-MPC2: Scalable, Robust World Models for Continuous Control
328. ICLR 2024Test-Time Adaptation with CLIP Reward for Zero-Shot Generalization in Vision-Language Models
329. ICLR 2024Text2Reward: Reward Shaping with Language Models for Reinforcement Learning
330. ICLR 2024The Curse of Diversity in Ensemble-Based Exploration
331. ICLR 2024The Effective Horizon Explains Deep RL Performance in Stochastic Environments
332. ICLR 2024The Generalization Gap in Offline Reinforcement Learning
333. ICLR 2024The Trickle-down Impact of Reward Inconsistency on RLHF
334. ICLR 2024The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning
335. ICLR 2024The Wasserstein Believer: Learning Belief Updates for Partially Observable Environments through Reliable Latent Space Models
336. ICLR 2024Thin-Shell Object Manipulations With Differentiable Physics Simulations
337. ICLR 2024Time-Efficient Reinforcement Learning with Stochastic Stateful Policies
338. ICLR 2024Time-Varying Propensity Score to Bridge the Gap between the Past and Present
339. ICLR 2024Tool-Augmented Reward Modeling
340. ICLR 2024TorchRL: A data-driven decision-making library for PyTorch
341. ICLR 2024Toward Optimal Policy Population Growth in Two-Player Zero-Sum Games
342. ICLR 2024Towards Assessing and Benchmarking Risk-Return Tradeoff of Off-Policy Evaluation
343. ICLR 2024Towards Imitation Learning to Branch for MIP: A Hybrid Reinforcement Learning based Sample Augmentation Approach
344. ICLR 2024Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback
345. ICLR 2024Towards Principled Representation Learning from Videos for Reinforcement Learning
346. ICLR 2024Towards Robust Offline Reinforcement Learning under Diverse Data Corruption
347. ICLR 2024Towards Understanding Sycophancy in Language Models
348. ICLR 2024Training Diffusion Models with Reinforcement Learning
349. ICLR 2024Transformers as Decision Makers: Provable In-Context Reinforcement Learning via Supervised Pretraining
350. ICLR 2024Tree Search-Based Policy Optimization under Stochastic Execution Delay

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.