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 32 of 42

1551. ICML 2024Hybrid Inverse Reinforcement Learning
1552. ICML 2024Hybrid Reinforcement Learning from Offline Observation Alone
1553. ICML 2024Implicit Bias of Policy Gradient in Linear Quadratic Control: Extrapolation to Unseen Initial States
1554. ICML 2024Improved Differentially Private and Lazy Online Convex Optimization: Lower Regret without Smoothness Requirements
1555. ICML 2024Improving Generalization in Offline Reinforcement Learning via Adversarial Data Splitting
1556. ICML 2024Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games
1557. ICML 2024Improving Token-Based World Models with Parallel Observation Prediction
1558. ICML 2024In value-based deep reinforcement learning, a pruned network is a good network
1559. ICML 2024In-Context Decision Transformer: Reinforcement Learning via Hierarchical Chain-of-Thought
1560. ICML 2024In-Context Learning Agents Are Asymmetric Belief Updaters
1561. ICML 2024In-Context Reinforcement Learning for Variable Action Spaces
1562. ICML 2024Individual Contributions as Intrinsic Exploration Scaffolds for Multi-agent Reinforcement Learning
1563. ICML 2024Inferring Dynamic Networks from Marginals with Iterative Proportional Fitting
1564. ICML 2024Inferring the Long-Term Causal Effects of Long-Term Treatments from Short-Term Experiments
1565. ICML 2024Information-Directed Pessimism for Offline Reinforcement Learning
1566. ICML 2024Investigating Pre-Training Objectives for Generalization in Vision-Based Reinforcement Learning
1567. ICML 2024INViT: A Generalizable Routing Problem Solver with Invariant Nested View Transformer
1568. ICML 2024Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study
1569. ICML 2024Is Inverse Reinforcement Learning Harder than Standard Reinforcement Learning? A Theoretical Perspective
1570. ICML 2024Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF
1571. ICML 2024Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-constraint
1572. ICML 2024Iterative Regularized Policy Optimization with Imperfect Demonstrations
1573. ICML 2024Just Cluster It: An Approach for Exploration in High-Dimensions using Clustering and Pre-Trained Representations
1574. ICML 2024LAGMA: LAtent Goal-guided Multi-Agent Reinforcement Learning
1575. ICML 2024Langevin Policy for Safe Reinforcement Learning
1576. ICML 2024Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game
1577. ICML 2024Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch
1578. ICML 2024Learning a Diffusion Model Policy from Rewards via Q-Score Matching
1579. ICML 2024Learning Causal Dynamics Models in Object-Oriented Environments
1580. ICML 2024Learning Constraints from Offline Demonstrations via Superior Distribution Correction Estimation
1581. ICML 2024Learning Coverage Paths in Unknown Environments with Deep Reinforcement Learning
1582. ICML 2024Learning Decision Policies with Instrumental Variables through Double Machine Learning
1583. ICML 2024Learning Decision Trees and Forests with Algorithmic Recourse
1584. ICML 2024Learning from Streaming Data when Users Choose
1585. ICML 2024Learning Latent Dynamic Robust Representations for World Models
1586. ICML 2024Learning Optimal Deterministic Policies with Stochastic Policy Gradients
1587. ICML 2024Learning Surrogates for Offline Black-Box Optimization via Gradient Matching
1588. ICML 2024Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making
1589. ICML 2024Learning the Target Network in Function Space
1590. ICML 2024Learning to Play Atari in a World of Tokens
1591. ICML 2024Learning to Reach Goals via Diffusion
1592. ICML 2024Learning to Stabilize Online Reinforcement Learning in Unbounded State Spaces
1593. ICML 2024Learning with 3D rotations, a hitchhiker's guide to SO(3)
1594. ICML 2024Limited Preference Aided Imitation Learning from Imperfect Demonstrations
1595. ICML 2024Linear Alignment: A Closed-form Solution for Aligning Human Preferences without Tuning and Feedback
1596. ICML 2024Linguistic Calibration of Long-Form Generations
1597. ICML 2024Listwise Reward Estimation for Offline Preference-based Reinforcement Learning
1598. ICML 2024LLM-Empowered State Representation for Reinforcement Learning
1599. ICML 2024Logistic Variational Bayes Revisited
1600. ICML 2024Major-Minor Mean Field Multi-Agent Reinforcement 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.