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 40 of 42

1951. ICML 2023Near-Optimal $\Phi$-Regret Learning in Extensive-Form Games
1952. ICML 2023Near-optimal Conservative Exploration in Reinforcement Learning under Episode-wise Constraints
1953. ICML 2023Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes
1954. ICML 2023Nested Elimination: A Simple Algorithm for Best-Item Identification From Choice-Based Feedback
1955. ICML 2023Neural Collapse in Deep Linear Networks: From Balanced to Imbalanced Data
1956. ICML 2023Non-stationary Reinforcement Learning under General Function Approximation
1957. ICML 2023Off-Policy Average Reward Actor-Critic with Deterministic Policy Search
1958. ICML 2023Offline Learning in Markov Games with General Function Approximation
1959. ICML 2023Offline Meta Reinforcement Learning with In-Distribution Online Adaptation
1960. ICML 2023Offline Reinforcement Learning with Closed-Form Policy Improvement Operators
1961. ICML 2023On Penalty-based Bilevel Gradient Descent Method
1962. ICML 2023On the Convergence of SARSA with Linear Function Approximation
1963. ICML 2023On the Effectiveness of Offline RL for Dialogue Response Generation
1964. ICML 2023On the Global Convergence of Risk-Averse Policy Gradient Methods with Expected Conditional Risk Measures
1965. ICML 2023On the Importance of Feature Decorrelation for Unsupervised Representation Learning in Reinforcement Learning
1966. ICML 2023On the Power of Pre-training for Generalization in RL: Provable Benefits and Hardness
1967. ICML 2023One-sided Matrix Completion from Two Observations Per Row
1968. ICML 2023Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning
1969. ICML 2023Optimal Horizon-Free Reward-Free Exploration for Linear Mixture MDPs
1970. ICML 2023Optimizing DDPM Sampling with Shortcut Fine-Tuning
1971. ICML 2023Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learning
1972. ICML 2023PAC-Bayesian Offline Contextual Bandits With Guarantees
1973. ICML 2023Parallel $Q$-Learning: Scaling Off-policy Reinforcement Learning under Massively Parallel Simulation
1974. ICML 2023Partially Observable Multi-agent RL with (Quasi-)Efficiency: The Blessing of Information Sharing
1975. ICML 2023Performative Reinforcement Learning
1976. ICML 2023PFNs4BO: In-Context Learning for Bayesian Optimization
1977. ICML 2023Policy Contrastive Imitation Learning
1978. ICML 2023Policy Evaluation and Temporal-Difference Learning in Continuous Time and Space: A Martingale Approach
1979. ICML 2023Policy Gradient in Robust MDPs with Global Convergence Guarantee
1980. ICML 2023Policy Regularization with Dataset Constraint for Offline Reinforcement Learning
1981. ICML 2023Posterior Sampling for Deep Reinforcement Learning
1982. ICML 2023PPG Reloaded: An Empirical Study on What Matters in Phasic Policy Gradient
1983. ICML 2023Predictable MDP Abstraction for Unsupervised Model-Based RL
1984. ICML 2023Predicting Rare Events by Shrinking Towards Proportional Odds
1985. ICML 2023Principled Offline RL in the Presence of Rich Exogenous Information
1986. ICML 2023Principled Reinforcement Learning with Human Feedback from Pairwise or K-wise Comparisons
1987. ICML 2023Prometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning
1988. ICML 2023Provable Benefit of Mixup for Finding Optimal Decision Boundaries
1989. ICML 2023Provable Reset-free Reinforcement Learning by No-Regret Reduction
1990. ICML 2023Provably Efficient Offline Reinforcement Learning with Perturbed Data Sources
1991. ICML 2023Provably Invariant Learning without Domain Information
1992. ICML 2023Q-learning Decision Transformer: Leveraging Dynamic Programming for Conditional Sequence Modelling in Offline RL
1993. ICML 2023QAS-Bench: Rethinking Quantum Architecture Search and A Benchmark
1994. ICML 2023Quantile Credit Assignment
1995. ICML 2023Quantum Policy Gradient Algorithm with Optimized Action Decoding
1996. ICML 2023RACE: Improve Multi-Agent Reinforcement Learning with Representation Asymmetry and Collaborative Evolution
1997. ICML 2023Reachability-Aware Laplacian Representation in Reinforcement Learning
1998. ICML 2023Regret Bounds for Markov Decision Processes with Recursive Optimized Certainty Equivalents
1999. ICML 2023Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice
2000. ICML 2023Reinforcement Learning Can Be More Efficient with Multiple Rewards

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.