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

2,494 papers, page 39 of 50

1901. NeurIPS 2024Rethinking Exploration in Reinforcement Learning with Effective Metric-Based Exploration Bonus
1902. NeurIPS 2024Rethinking Inverse Reinforcement Learning: from Data Alignment to Task Alignment
1903. NeurIPS 2024Rethinking Model-based, Policy-based, and Value-based Reinforcement Learning via the Lens of Representation Complexity
1904. NeurIPS 2024Rethinking Optimal Transport in Offline Reinforcement Learning
1905. NeurIPS 2024Reward Machines for Deep RL in Noisy and Uncertain Environments
1906. NeurIPS 2024RGMDT: Return-Gap-Minimizing Decision Tree Extraction in Non-Euclidean Metric Space
1907. NeurIPS 2024Risk-Averse Fine-tuning of Large Language Models
1908. NeurIPS 2024Risk-sensitive control as inference with Rényi divergence
1909. NeurIPS 2024RL in Latent MDPs is Tractable: Online Guarantees via Off-Policy Evaluation
1910. NeurIPS 2024RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold
1911. NeurIPS 2024RL-GPT: Integrating Reinforcement Learning and Code-as-policy
1912. NeurIPS 2024Robot Policy Learning with Temporal Optimal Transport Reward
1913. NeurIPS 2024Robust Reinforcement Learning from Corrupted Human Feedback
1914. NeurIPS 2024Robust Reinforcement Learning with General Utility
1915. NeurIPS 2024ROIDICE: Offline Return on Investment Maximization for Efficient Decision Making
1916. NeurIPS 2024RoME: A Robust Mixed-Effects Bandit Algorithm for Optimizing Mobile Health Interventions
1917. NeurIPS 2024Rule Based Rewards for Language Model Safety
1918. NeurIPS 2024Safe and Efficient: A Primal-Dual Method for Offline Convex CMDPs under Partial Data Coverage
1919. NeurIPS 2024Safety through feedback in Constrained RL
1920. NeurIPS 2024Sample Complexity Reduction via Policy Difference Estimation in Tabular Reinforcement Learning
1921. NeurIPS 2024Sample-Efficient Agnostic Boosting
1922. NeurIPS 2024Sample-Efficient Constrained Reinforcement Learning with General Parameterization
1923. NeurIPS 2024SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning
1924. NeurIPS 2024Scalable and Effective Arithmetic Tree Generation for Adder and Multiplier Designs
1925. NeurIPS 2024Scalable Constrained Policy Optimization for Safe Multi-agent Reinforcement Learning
1926. NeurIPS 2024Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms
1927. NeurIPS 2024SCaR: Refining Skill Chaining for Long-Horizon Robotic Manipulation via Dual Regularization
1928. NeurIPS 2024SeeA*: Efficient Exploration-Enhanced A* Search by Selective Sampling
1929. NeurIPS 2024Seek Commonality but Preserve Differences: Dissected Dynamics Modeling for Multi-modal Visual RL
1930. NeurIPS 2024Self-Play Fine-tuning of Diffusion Models for Text-to-image Generation
1931. NeurIPS 2024Self-playing Adversarial Language Game Enhances LLM Reasoning
1932. NeurIPS 2024Sequential Decision Making with Expert Demonstrations under Unobserved Heterogeneity
1933. NeurIPS 2024Shared Autonomy with IDA: Interventional Diffusion Assistance
1934. NeurIPS 2024Simplifying Constraint Inference with Inverse Reinforcement Learning
1935. NeurIPS 2024Simplifying Latent Dynamics with Softly State-Invariant World Models
1936. NeurIPS 2024SimPO: Simple Preference Optimization with a Reference-Free Reward
1937. NeurIPS 2024SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions
1938. NeurIPS 2024Skill-aware Mutual Information Optimisation for Zero-shot Generalisation in Reinforcement Learning
1939. NeurIPS 2024SleeperNets: Universal Backdoor Poisoning Attacks Against Reinforcement Learning Agents
1940. NeurIPS 2024Solving Minimum-Cost Reach Avoid using Reinforcement Learning
1941. NeurIPS 2024Solving Zero-Sum Markov Games with Continuous State via Spectral Dynamic Embedding
1942. NeurIPS 2024Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs
1943. NeurIPS 2024Speaking Your Language: Spatial Relationships in Interpretable Emergent Communication
1944. NeurIPS 2024Spectral-Risk Safe Reinforcement Learning with Convergence Guarantees
1945. NeurIPS 2024Speculative Monte-Carlo Tree Search
1946. NeurIPS 2024SPO: Sequential Monte Carlo Policy Optimisation
1947. NeurIPS 2024SPRINQL: Sub-optimal Demonstrations driven Offline Imitation Learning
1948. NeurIPS 2024State Chrono Representation for Enhancing Generalization in Reinforcement Learning
1949. NeurIPS 2024State-free Reinforcement Learning
1950. NeurIPS 2024Statistical Efficiency of Distributional Temporal Difference 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.