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 34 of 37

1651. ICLR 2023Does Zero-Shot Reinforcement Learning Exist?
1652. ICLR 2023Dynamic Update-to-Data Ratio: Minimizing World Model Overfitting
1653. ICLR 2023Efficient Deep Reinforcement Learning Requires Regulating Overfitting
1654. ICLR 2023Efficient Offline Policy Optimization with a Learned Model
1655. ICLR 2023Efficient Planning in a Compact Latent Action Space
1656. ICLR 2023Efficiently Computing Nash Equilibria in Adversarial Team Markov Games
1657. ICLR 2023Emergence of Maps in the Memories of Blind Navigation Agents
1658. ICLR 2023ERL-Re$^2$: Efficient Evolutionary Reinforcement Learning with Shared State Representation and Individual Policy Representation
1659. ICLR 2023ESCHER: Eschewing Importance Sampling in Games by Computing a History Value Function to Estimate Regret
1660. ICLR 2023EUCLID: Towards Efficient Unsupervised Reinforcement Learning with Multi-choice Dynamics Model
1661. ICLR 2023Evaluating Long-Term Memory in 3D Mazes
1662. ICLR 2023Evolving Populations of Diverse RL Agents with MAP-Elites
1663. ICLR 2023Explaining RL Decisions with Trajectories
1664. ICLR 2023Extreme Q-Learning: MaxEnt RL without Entropy
1665. ICLR 2023Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems
1666. ICLR 2023Faster Last-iterate Convergence of Policy Optimization in Zero-Sum Markov Games
1667. ICLR 2023FluidLab: A Differentiable Environment for Benchmarking Complex Fluid Manipulation
1668. ICLR 2023From $t$-SNE to UMAP with contrastive learning
1669. ICLR 2023From Play to Policy: Conditional Behavior Generation from Uncurated Robot Data
1670. ICLR 2023Generalize Learned Heuristics to Solve Large-scale Vehicle Routing Problems in Real-time
1671. ICLR 2023Generating Diverse Cooperative Agents by Learning Incompatible Policies
1672. ICLR 2023Generative Augmented Flow Networks
1673. ICLR 2023GFlowNets and variational inference
1674. ICLR 2023GoBigger: A Scalable Platform for Cooperative-Competitive Multi-Agent Interactive Simulation
1675. ICLR 2023Graph-based Deterministic Policy Gradient for Repetitive Combinatorial Optimization Problems
1676. ICLR 2023Gray-Box Gaussian Processes for Automated Reinforcement Learning
1677. ICLR 2023Greedy Actor-Critic: A New Conditional Cross-Entropy Method for Policy Improvement
1678. ICLR 2023Guarded Policy Optimization with Imperfect Online Demonstrations
1679. ICLR 2023Guiding Safe Exploration with Weakest Preconditions
1680. ICLR 2023Harnessing Mixed Offline Reinforcement Learning Datasets via Trajectory Weighting
1681. ICLR 2023HiT-MDP: Learning the SMDP option framework on MDPs with Hidden Temporal Embeddings
1682. ICLR 2023Human-level Atari 200x faster
1683. ICLR 2023Hybrid RL: Using both offline and online data can make RL efficient
1684. ICLR 2023Hyper-Decision Transformer for Efficient Online Policy Adaptation
1685. ICLR 2023Hyperbolic Deep Reinforcement Learning
1686. ICLR 2023Imitating Graph-Based Planning with Goal-Conditioned Policies
1687. ICLR 2023Impossibly Good Experts and How to Follow Them
1688. ICLR 2023Improved Sample Complexity for Reward-free Reinforcement Learning under Low-rank MDPs
1689. ICLR 2023Improving Deep Policy Gradients with Value Function Search
1690. ICLR 2023In-context Reinforcement Learning with Algorithm Distillation
1691. ICLR 2023In-sample Actor Critic for Offline Reinforcement Learning
1692. ICLR 2023Interaction-Based Disentanglement of Entities for Object-Centric World Models
1693. ICLR 2023Investigating Multi-task Pretraining and Generalization in Reinforcement Learning
1694. ICLR 2023Is Conditional Generative Modeling all you need for Decision Making?
1695. ICLR 2023Is Model Ensemble Necessary? Model-based RL via a Single Model with Lipschitz Regularized Value Function
1696. ICLR 2023Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization
1697. ICLR 2023Latent State Marginalization as a Low-cost Approach for Improving Exploration
1698. ICLR 2023Latent Variable Representation for Reinforcement Learning
1699. ICLR 2023Learnable Behavior Control: Breaking Atari Human World Records via Sample-Efficient Behavior Selection
1700. ICLR 2023Learning a Data-Driven Policy Network for Pre-Training Automated Feature Engineering

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.