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

1,827 papers, page 30 of 37

1451. ICLR 2024Multimodal Web Navigation with Instruction-Finetuned Foundation Models
1452. ICLR 2024Negatively Correlated Ensemble Reinforcement Learning for Online Diverse Game Level Generation
1453. ICLR 2024ODICE: Revealing the Mystery of Distribution Correction Estimation via Orthogonal-gradient Update
1454. ICLR 2024Off-Policy Primal-Dual Safe Reinforcement Learning
1455. ICLR 2024Offline Data Enhanced On-Policy Policy Gradient with Provable Guarantees
1456. ICLR 2024Offline RL with Observation Histories: Analyzing and Improving Sample Complexity
1457. ICLR 2024OMNI: Open-endedness via Models of human Notions of Interestingness
1458. ICLR 2024On Double Descent in Reinforcement Learning with LSTD and Random Features
1459. ICLR 2024On Representation Complexity of Model-based and Model-free Reinforcement Learning
1460. ICLR 2024On Stationary Point Convergence of PPO-Clip
1461. ICLR 2024On the Expressivity of Objective-Specification Formalisms in Reinforcement Learning
1462. ICLR 2024On the Hardness of Constrained Cooperative Multi-Agent Reinforcement Learning
1463. ICLR 2024On the Joint Interaction of Models, Data, and Features
1464. ICLR 2024On the Role of General Function Approximation in Offline Reinforcement Learning
1465. ICLR 2024On Trajectory Augmentations for Off-Policy Evaluation
1466. ICLR 2024On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes
1467. ICLR 2024Open the Black Box: Step-based Policy Updates for Temporally-Correlated Episodic Reinforcement Learning
1468. ICLR 2024OpenChat: Advancing Open-source Language Models with Mixed-Quality Data
1469. ICLR 2024Optimal Sample Complexity for Average Reward Markov Decision Processes
1470. ICLR 2024PAE: Reinforcement Learning from External Knowledge for Efficient Exploration
1471. ICLR 2024PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback
1472. ICLR 2024Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning
1473. ICLR 2024Physics-Regulated Deep Reinforcement Learning: Invariant Embeddings
1474. ICLR 2024Piecewise Linear Parametrization of Policies: Towards Interpretable Deep Reinforcement Learning
1475. ICLR 2024PILOT: An $\mathcal{O}(1/K)$-Convergent Approach for Policy Evaluation with Nonlinear Function Approximation
1476. ICLR 2024Plan-Seq-Learn: Language Model Guided RL for Solving Long Horizon Robotics Tasks
1477. ICLR 2024Plug-and-Play Policy Planner for Large Language Model Powered Dialogue Agents
1478. ICLR 2024Policy Rehearsing: Training Generalizable Policies for Reinforcement Learning
1479. ICLR 2024Pre-Training and Fine-Tuning Generative Flow Networks
1480. ICLR 2024Pre-Training Goal-based Models for Sample-Efficient Reinforcement Learning
1481. ICLR 2024Pre-training with Synthetic Data Helps Offline Reinforcement Learning
1482. ICLR 2024Predictive auxiliary objectives in deep RL mimic learning in the brain
1483. ICLR 2024Prioritized Soft Q-Decomposition for Lexicographic Reinforcement Learning
1484. ICLR 2024Privately Aligning Language Models with Reinforcement Learning
1485. ICLR 2024Privileged Sensing Scaffolds Reinforcement Learning
1486. ICLR 2024Proper Laplacian Representation Learning
1487. ICLR 2024Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo
1488. ICLR 2024Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes
1489. ICLR 2024Provable Memory Efficient Self-Play Algorithm for Model-free Reinforcement Learning
1490. ICLR 2024Provable Offline Preference-Based Reinforcement Learning
1491. ICLR 2024Provable Reward-Agnostic Preference-Based Reinforcement Learning
1492. ICLR 2024Provably Efficient CVaR RL in Low-rank MDPs
1493. ICLR 2024Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation and Human Feedback
1494. ICLR 2024Provably Efficient UCB-type Algorithms For Learning Predictive State Representations
1495. ICLR 2024Proximal Policy Gradient Arborescence for Quality Diversity Reinforcement Learning
1496. ICLR 2024Quantifying the Sensitivity of Inverse Reinforcement Learning to Misspecification
1497. ICLR 2024Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL
1498. ICLR 2024Query-Policy Misalignment in Preference-Based Reinforcement Learning
1499. ICLR 2024RAIN: Your Language Models Can Align Themselves without Finetuning
1500. ICLR 2024RAPPER: Reinforced Rationale-Prompted Paradigm for Natural Language Explanation in Visual Question Answering

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.