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

2,494 papers, page 49 of 50

2401. NeurIPS 2023Sample Complexity for Quadratic Bandits: Hessian Dependent Bounds and Optimal Algorithms
2402. NeurIPS 2023Sample Complexity of Goal-Conditioned Hierarchical Reinforcement Learning
2403. NeurIPS 2023Sample Efficient Reinforcement Learning in Mixed Systems through Augmented Samples and Its Applications to Queueing Networks
2404. NeurIPS 2023Sample-Efficient and Safe Deep Reinforcement Learning via Reset Deep Ensemble Agents
2405. NeurIPS 2023Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent
2406. NeurIPS 2023SARAMIS: Simulation Assets for Robotic Assisted and Minimally Invasive Surgery
2407. NeurIPS 2023Scalable Primal-Dual Actor-Critic Method for Safe Multi-Agent RL with General Utilities
2408. NeurIPS 2023Scalarization for Multi-Task and Multi-Domain Learning at Scale
2409. NeurIPS 2023ScenarioNet: Open-Source Platform for Large-Scale Traffic Scenario Simulation and Modeling
2410. NeurIPS 2023Seeing is not Believing: Robust Reinforcement Learning against Spurious Correlation
2411. NeurIPS 2023SEENN: Towards Temporal Spiking Early Exit Neural Networks
2412. NeurIPS 2023Selectively Sharing Experiences Improves Multi-Agent Reinforcement Learning
2413. NeurIPS 2023Self-Predictive Universal AI
2414. NeurIPS 2023Self-Refine: Iterative Refinement with Self-Feedback
2415. NeurIPS 2023Self-Supervised Reinforcement Learning that Transfers using Random Features
2416. NeurIPS 2023Semantic HELM: A Human-Readable Memory for Reinforcement Learning
2417. NeurIPS 2023Sequential Preference Ranking for Efficient Reinforcement Learning from Human Feedback
2418. NeurIPS 2023SHOT: Suppressing the Hessian along the Optimization Trajectory for Gradient-Based Meta-Learning
2419. NeurIPS 2023SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning
2420. NeurIPS 2023Small batch deep reinforcement learning
2421. NeurIPS 2023Social Motion Prediction with Cognitive Hierarchies
2422. NeurIPS 2023Solving a Class of Non-Convex Minimax Optimization in Federated Learning
2423. NeurIPS 2023Sorting with Predictions
2424. NeurIPS 2023Sparse Graph Learning from Spatiotemporal Time Series
2425. NeurIPS 2023Spatially Resolved Gene Expression Prediction from Histology Images via Bi-modal Contrastive Learning
2426. NeurIPS 2023Spectral Entry-wise Matrix Estimation for Low-Rank Reinforcement Learning
2427. NeurIPS 2023SPQR: Controlling Q-ensemble Independence with Spiked Random Model for Reinforcement Learning
2428. NeurIPS 2023SPRING: Studying Papers and Reasoning to play Games
2429. NeurIPS 2023State Regularized Policy Optimization on Data with Dynamics Shift
2430. NeurIPS 2023State Sequences Prediction via Fourier Transform for Representation Learning
2431. NeurIPS 2023State-Action Similarity-Based Representations for Off-Policy Evaluation
2432. NeurIPS 2023State2Explanation: Concept-Based Explanations to Benefit Agent Learning and User Understanding
2433. NeurIPS 2023StateMask: Explaining Deep Reinforcement Learning through State Mask
2434. NeurIPS 2023STEVE-1: A Generative Model for Text-to-Behavior in Minecraft
2435. NeurIPS 2023Stochastic Approximation Approaches to Group Distributionally Robust Optimization
2436. NeurIPS 2023STORM: Efficient Stochastic Transformer based World Models for Reinforcement Learning
2437. NeurIPS 2023Strategic Apple Tasting
2438. NeurIPS 2023Structured State Space Models for In-Context Reinforcement Learning
2439. NeurIPS 2023Successor-Predecessor Intrinsic Exploration
2440. NeurIPS 2023Suggesting Variable Order for Cylindrical Algebraic Decomposition via Reinforcement Learning
2441. NeurIPS 2023Supervised Pretraining Can Learn In-Context Reinforcement Learning
2442. NeurIPS 2023Supported Value Regularization for Offline Reinforcement Learning
2443. NeurIPS 2023Survival Instinct in Offline Reinforcement Learning
2444. NeurIPS 2023SustainGym: Reinforcement Learning Environments for Sustainable Energy Systems
2445. NeurIPS 2023Swarm Reinforcement Learning for Adaptive Mesh Refinement
2446. NeurIPS 2023Synthetic Experience Replay
2447. NeurIPS 2023T2T: From Distribution Learning in Training to Gradient Search in Testing for Combinatorial Optimization
2448. NeurIPS 2023Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds
2449. NeurIPS 2023Task-aware world model learning with meta weighting via bi-level optimization
2450. NeurIPS 2023TaskMet: Task-driven Metric Learning for Model Learning

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.