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 36 of 42

1751. ICML 2024Switching the Loss Reduces the Cost in Batch Reinforcement Learning
1752. ICML 2024Symmetric Replay Training: Enhancing Sample Efficiency in Deep Reinforcement Learning for Combinatorial Optimization
1753. ICML 2024Tackling Non-Stationarity in Reinforcement Learning via Causal-Origin Representation
1754. ICML 2024Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation
1755. ICML 2024Temporal Logic Specification-Conditioned Decision Transformer for Offline Safe Reinforcement Learning
1756. ICML 2024Test-Time Regret Minimization in Meta Reinforcement Learning
1757. ICML 2024The Max-Min Formulation of Multi-Objective Reinforcement Learning: From Theory to a Model-Free Algorithm
1758. ICML 2024The Non-linear $F$-Design and Applications to Interactive Learning
1759. ICML 2024To the Max: Reinventing Reward in Reinforcement Learning
1760. ICML 2024Towards Efficient Exact Optimization of Language Model Alignment
1761. ICML 2024Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph
1762. ICML 2024Towards Global Optimality for Practical Average Reward Reinforcement Learning without Mixing Time Oracles
1763. ICML 2024Towards Optimal Adversarial Robust Q-learning with Bellman Infinity-error
1764. ICML 2024Towards Robust Model-Based Reinforcement Learning Against Adversarial Corruption
1765. ICML 2024Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial Optimization
1766. ICML 2024Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning
1767. ICML 2024Truly No-Regret Learning in Constrained MDPs
1768. ICML 2024Trust the Model Where It Trusts Itself - Model-Based Actor-Critic with Uncertainty-Aware Rollout Adaption
1769. ICML 2024Trustworthy Alignment of Retrieval-Augmented Large Language Models via Reinforcement Learning
1770. ICML 2024ULTRAFEEDBACK: Boosting Language Models with Scaled AI Feedback
1771. ICML 2024Uncertainty-Aware Reward-Free Exploration with General Function Approximation
1772. ICML 2024Understanding and Diagnosing Deep Reinforcement Learning
1773. ICML 2024Unlock the Cognitive Generalization of Deep Reinforcement Learning via Granular Ball Representation
1774. ICML 2024Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings
1775. ICML 2024Value-Evolutionary-Based Reinforcement Learning
1776. ICML 2024WARM: On the Benefits of Weight Averaged Reward Models
1777. ICML 2024Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision
1778. ICML 2024When Do Skills Help Reinforcement Learning? A Theoretical Analysis of Temporal Abstractions
1779. ICML 2024When is Transfer Learning Possible?
1780. ICML 2024Why Do Animals Need Shaping? A Theory of Task Composition and Curriculum Learning
1781. ICML 2024Zero-Shot Reinforcement Learning via Function Encoders
1782. ICML 2024Zero-Sum Positional Differential Games as a Framework for Robust Reinforcement Learning: Deep Q-Learning Approach
1783. ICML 2023A Connection between One-Step RL and Critic Regularization in Reinforcement Learning
1784. ICML 2023A Coupled Flow Approach to Imitation Learning
1785. ICML 2023A Game-Theoretic Framework for Managing Risk in Multi-Agent Systems
1786. ICML 2023A Near-Optimal Algorithm for Safe Reinforcement Learning Under Instantaneous Hard Constraints
1787. ICML 2023A Reinforcement Learning Framework for Dynamic Mediation Analysis
1788. ICML 2023A Robust Test for the Stationarity Assumption in Sequential Decision Making
1789. ICML 2023A Universal Unbiased Method for Classification from Aggregate Observations
1790. ICML 2023Abstracting Imperfect Information Away from Two-Player Zero-Sum Games
1791. ICML 2023Action Matching: Learning Stochastic Dynamics from Samples
1792. ICML 2023Active Policy Improvement from Multiple Black-box Oracles
1793. ICML 2023Actor-Critic Alignment for Offline-to-Online Reinforcement Learning
1794. ICML 2023AdaptDiffuser: Diffusion Models as Adaptive Self-evolving Planners
1795. ICML 2023Adaptive Barrier Smoothing for First-Order Policy Gradient with Contact Dynamics
1796. ICML 2023Adversarial Cheap Talk
1797. ICML 2023Adversarial Learning of Distributional Reinforcement Learning
1798. ICML 2023Aligning Language Models with Preferences through $f$-divergence Minimization
1799. ICML 2023An Adaptive Entropy-Regularization Framework for Multi-Agent Reinforcement Learning
1800. ICML 2023An Investigation into Pre-Training Object-Centric Representations for 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.