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

1,070 papers, page 16 of 22

751. NeurIPS 2023FlowPG: Action-constrained Policy Gradient with Normalizing Flows
752. NeurIPS 2023For SALE: State-Action Representation Learning for Deep Reinforcement Learning
753. NeurIPS 2023Fractal Landscapes in Policy Optimization
754. NeurIPS 2023From Pixels to UI Actions: Learning to Follow Instructions via Graphical User Interfaces
755. NeurIPS 2023Future-Dependent Value-Based Off-Policy Evaluation in POMDPs
756. NeurIPS 2023Game Solving with Online Fine-Tuning
757. NeurIPS 2023General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence
758. NeurIPS 2023Generalized Weighted Path Consistency for Mastering Atari Games
759. NeurIPS 2023Generating Behaviorally Diverse Policies with Latent Diffusion Models
760. NeurIPS 2023Generative Modelling of Stochastic Actions with Arbitrary Constraints in Reinforcement Learning
761. NeurIPS 2023Generator Born from Classifier
762. NeurIPS 2023Gigastep - One Billion Steps per Second Multi-agent Reinforcement Learning
763. NeurIPS 2023Global Identifiability of $\ell_1$-based Dictionary Learning via Matrix Volume Optimization
764. NeurIPS 2023Goal-conditioned Offline Planning from Curious Exploration
765. NeurIPS 2023Goal-Conditioned Predictive Coding for Offline Reinforcement Learning
766. NeurIPS 2023Gradient Informed Proximal Policy Optimization
767. NeurIPS 2023Guide Your Agent with Adaptive Multimodal Rewards
768. NeurIPS 2023Guiding Large Language Models via Directional Stimulus Prompting
769. NeurIPS 2023H-InDex: Visual Reinforcement Learning with Hand-Informed Representations for Dexterous Manipulation
770. NeurIPS 2023Harnessing the power of choices in decision tree learning
771. NeurIPS 2023Hierarchical Adaptive Value Estimation for Multi-modal Visual Reinforcement Learning
772. NeurIPS 2023Hierarchical Multi-Agent Skill Discovery
773. NeurIPS 2023HIQL: Offline Goal-Conditioned RL with Latent States as Actions
774. NeurIPS 2023Hokoff: Real Game Dataset from Honor of Kings and its Offline Reinforcement Learning Benchmarks
775. NeurIPS 2023Honesty Is the Best Policy: Defining and Mitigating AI Deception
776. NeurIPS 2023How to Fine-tune the Model: Unified Model Shift and Model Bias Policy Optimization
777. NeurIPS 2023Hybrid Policy Optimization from Imperfect Demonstrations
778. NeurIPS 2023Hybrid Search for Efficient Planning with Completeness Guarantees
779. NeurIPS 2023Hyperbolic Space with Hierarchical Margin Boosts Fine-Grained Learning from Coarse Labels
780. NeurIPS 2023Hyperbolic VAE via Latent Gaussian Distributions
781. NeurIPS 2023Hypervolume Maximization: A Geometric View of Pareto Set Learning
782. NeurIPS 2023Imitation Learning from Imperfection: Theoretical Justifications and Algorithms
783. NeurIPS 2023Imitation Learning from Vague Feedback
784. NeurIPS 2023IMP-MARL: a Suite of Environments for Large-scale Infrastructure Management Planning via MARL
785. NeurIPS 2023Importance Weighted Actor-Critic for Optimal Conservative Offline Reinforcement Learning
786. NeurIPS 2023Importance-aware Co-teaching for Offline Model-based Optimization
787. NeurIPS 2023Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning
788. NeurIPS 2023Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates
789. NeurIPS 2023Inferring the Future by Imagining the Past
790. NeurIPS 2023Information Design in Multi-Agent Reinforcement Learning
791. NeurIPS 2023Information Maximizing Curriculum: A Curriculum-Based Approach for Learning Versatile Skills
792. NeurIPS 2023Instructing Goal-Conditioned Reinforcement Learning Agents with Temporal Logic Objectives
793. NeurIPS 2023Interaction Measures, Partition Lattices and Kernel Tests for High-Order Interactions
794. NeurIPS 2023InterCode: Standardizing and Benchmarking Interactive Coding with Execution Feedback
795. NeurIPS 2023Interpretable and Explainable Logical Policies via Neurally Guided Symbolic Abstraction
796. NeurIPS 2023Interpretable Reward Redistribution in Reinforcement Learning: A Causal Approach
797. NeurIPS 2023Inverse Preference Learning: Preference-based RL without a Reward Function
798. NeurIPS 2023Inverse Reinforcement Learning with the Average Reward Criterion
799. NeurIPS 2023Is RLHF More Difficult than Standard RL? A Theoretical Perspective
800. NeurIPS 2023Iterative Reachability Estimation for Safe 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.