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

1,190 papers, page 18 of 24

851. NeurIPS 2024Efficient Recurrent Off-Policy RL Requires a Context-Encoder-Specific Learning Rate
852. NeurIPS 2024Efficient Reinforcement Learning by Discovering Neural Pathways
853. NeurIPS 2024Embedding-Aligned Language Models
854. NeurIPS 2024Enabling Adaptive Agent Training in Open-Ended Simulators by Targeting Diversity
855. NeurIPS 2024Enhancing Chess Reinforcement Learning with Graph Representation
856. NeurIPS 2024Enhancing Efficiency of Safe Reinforcement Learning via Sample Manipulation
857. NeurIPS 2024Enhancing Multiple Dimensions of Trustworthiness in LLMs via Sparse Activation Control
858. NeurIPS 2024Enhancing Robustness in Deep Reinforcement Learning: A Lyapunov Exponent Approach
859. NeurIPS 2024Enhancing Robustness of Graph Neural Networks on Social Media with Explainable Inverse Reinforcement Learning
860. NeurIPS 2024Entropy-regularized Diffusion Policy with Q-Ensembles for Offline Reinforcement Learning
861. NeurIPS 2024EpiCare: A Reinforcement Learning Benchmark for Dynamic Treatment Regimes
862. NeurIPS 2024Episodic Future Thinking Mechanism for Multi-agent Reinforcement Learning
863. NeurIPS 2024Excluding the Irrelevant: Focusing Reinforcement Learning through Continuous Action Masking
864. NeurIPS 2024Exclusively Penalized Q-learning for Offline Reinforcement Learning
865. NeurIPS 2024Expectation Alignment: Handling Reward Misspecification in the Presence of Expectation Mismatch
866. NeurIPS 2024Exploiting the Replay Memory Before Exploring the Environment: Enhancing Reinforcement Learning Through Empirical MDP Iteration
867. NeurIPS 2024Exploration by Learning Diverse Skills through Successor State Representations
868. NeurIPS 2024Exploratory Retrieval-Augmented Planning For Continual Embodied Instruction Following
869. NeurIPS 2024Exploring the Edges of Latent State Clusters for Goal-Conditioned Reinforcement Learning
870. NeurIPS 2024FactorSim: Generative Simulation via Factorized Representation
871. NeurIPS 2024Fast TRAC: A Parameter-Free Optimizer for Lifelong Reinforcement Learning
872. NeurIPS 2024Federated Ensemble-Directed Offline Reinforcement Learning
873. NeurIPS 2024Federated Natural Policy Gradient and Actor Critic Methods for Multi-task Reinforcement Learning
874. NeurIPS 2024Feint Behaviors and Strategies: Formalization, Implementation and Evaluation
875. NeurIPS 2024Few-Shot Task Learning through Inverse Generative Modeling
876. NeurIPS 2024Finding good policies in average-reward Markov Decision Processes without prior knowledge
877. NeurIPS 2024Fine Tuning Out-of-Vocabulary Item Recommendation with User Sequence Imagination
878. NeurIPS 2024Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning
879. NeurIPS 2024First-Explore, then Exploit: Meta-Learning to Solve Hard Exploration-Exploitation Trade-Offs
880. NeurIPS 2024FLAME : Factuality-Aware Alignment for Large Language Models
881. NeurIPS 2024FlexPlanner: Flexible 3D Floorplanning via Deep Reinforcement Learning in Hybrid Action Space with Multi-Modality Representation
882. NeurIPS 2024Flipping-based Policy for Chance-Constrained Markov Decision Processes
883. NeurIPS 2024Focus On What Matters: Separated Models For Visual-Based RL Generalization
884. NeurIPS 2024Foundations of Multivariate Distributional Reinforcement Learning
885. NeurIPS 2024From Text to Trajectory: Exploring Complex Constraint Representation and Decomposition in Safe Reinforcement Learning
886. NeurIPS 2024Functional Bilevel Optimization for Machine Learning
887. NeurIPS 2024GarmentLab: A Unified Simulation and Benchmark for Garment Manipulation
888. NeurIPS 2024Generalizing Consistency Policy to Visual RL with Prioritized Proximal Experience Regularization
889. NeurIPS 2024Generating Code World Models with Large Language Models Guided by Monte Carlo Tree Search
890. NeurIPS 2024GenRL: Multimodal-foundation world models for generalization in embodied agents
891. NeurIPS 2024Geometric-Averaged Preference Optimization for Soft Preference Labels
892. NeurIPS 2024Getting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT for LLM Alignment
893. NeurIPS 2024Goal Conditioned Reinforcement Learning for Photo Finishing Tuning
894. NeurIPS 2024Goal-Conditioned On-Policy Reinforcement Learning
895. NeurIPS 2024Going Beyond Heuristics by Imposing Policy Improvement as a Constraint
896. NeurIPS 2024GOMAA-Geo: GOal Modality Agnostic Active Geo-localization
897. NeurIPS 2024Gradient Cuff: Detecting Jailbreak Attacks on Large Language Models by Exploring Refusal Loss Landscapes
898. NeurIPS 2024Gradient-Free Methods for Nonconvex Nonsmooth Stochastic Compositional Optimization
899. NeurIPS 2024Graph Diffusion Policy Optimization
900. NeurIPS 2024Graph Learning for Numeric Planning

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.