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

304 papers, page 2 of 7

51. ICLR 2024CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity
52. ICLR 2024Curiosity-driven Red-teaming for Large Language Models
53. ICLR 2024Curriculum reinforcement learning for quantum architecture search under hardware errors
54. ICLR 2024Cycle Consistency Driven Object Discovery
55. ICLR 2024Decision ConvFormer: Local Filtering in MetaFormer is Sufficient for Decision Making
56. ICLR 2024Decoupling regularization from the action space
57. ICLR 2024Deep Reinforcement Learning for Modelling Protein Complexes
58. ICLR 2024Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling
59. ICLR 2024Defining and extracting generalizable interaction primitives from DNNs
60. ICLR 2024Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding
61. ICLR 2024Demonstration-Regularized RL
62. ICLR 2024Demystifying Linear MDPs and Novel Dynamics Aggregation Framework
63. ICLR 2024Designing Skill-Compatible AI: Methodologies and Frameworks in Chess
64. ICLR 2024Detecting Pretraining Data from Large Language Models
65. ICLR 2024DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models
66. ICLR 2024Directly Fine-Tuning Diffusion Models on Differentiable Rewards
67. ICLR 2024Discovering Temporally-Aware Reinforcement Learning Algorithms
68. ICLR 2024Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF
69. ICLR 2024DittoGym: Learning to Control Soft Shape-Shifting Robots
70. ICLR 2024Diverse Projection Ensembles for Distributional Reinforcement Learning
71. ICLR 2024DMBP: Diffusion model-based predictor for robust offline reinforcement learning against state observation perturbations
72. ICLR 2024Domain Randomization via Entropy Maximization
73. ICLR 2024DreamSmooth: Improving Model-based Reinforcement Learning via Reward Smoothing
74. ICLR 2024DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization
75. ICLR 2024Dual RL: Unification and New Methods for Reinforcement and Imitation Learning
76. ICLR 2024Duolando: Follower GPT with Off-Policy Reinforcement Learning for Dance Accompaniment
77. ICLR 2024Dynamic Layer Tying for Parameter-Efficient Transformers
78. ICLR 2024Dynamic Neighborhood Construction for Structured Large Discrete Action Spaces
79. ICLR 2024Efficient Dynamics Modeling in Interactive Environments with Koopman Theory
80. ICLR 2024Efficient Episodic Memory Utilization of Cooperative Multi-Agent Reinforcement Learning
81. ICLR 2024Efficient Inverse Multiagent Learning
82. ICLR 2024Efficient Multi-agent Reinforcement Learning by Planning
83. ICLR 2024Efficient Planning with Latent Diffusion
84. ICLR 2024Enabling Lanuguage Models to Implicitly Learn Self-Improvement
85. ICLR 2024Enhancing Human Experience in Human-Agent Collaboration: A Human-Centered Modeling Approach Based on Positive Human Gain
86. ICLR 2024Enhancing Human-AI Collaboration Through Logic-Guided Reasoning
87. ICLR 2024Entity-Centric Reinforcement Learning for Object Manipulation from Pixels
88. ICLR 2024Eureka: Human-Level Reward Design via Coding Large Language Models
89. ICLR 2024Explaining Kernel Clustering via Decision Trees
90. ICLR 2024Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning
91. ICLR 2024Exploring the Promise and Limits of Real-Time Recurrent Learning
92. ICLR 2024Fast Hyperboloid Decision Tree Algorithms
93. ICLR 2024Fast Imitation via Behavior Foundation Models
94. ICLR 2024Fast Value Tracking for Deep Reinforcement Learning
95. ICLR 2024Federated Q-Learning: Linear Regret Speedup with Low Communication Cost
96. ICLR 2024Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning
97. ICLR 2024First-order ANIL provably learns representations despite overparametrisation
98. ICLR 2024FLD: Fourier Latent Dynamics for Structured Motion Representation and Learning
99. ICLR 2024Flow to Better: Offline Preference-based Reinforcement Learning via Preferred Trajectory Generation
100. ICLR 2024Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised 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.