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

784 papers, page 2 of 16

51. NeurIPS 2025AlphaZero Neural Scaling and Zipf's Law: a Tale of Board Games and Power Laws
52. NeurIPS 2025AMBER: Adaptive Mesh Generation by Iterative Mesh Resolution Prediction
53. NeurIPS 2025Analytic Energy-Guided Policy Optimization for Offline Reinforcement Learning
54. NeurIPS 2025Angles Don’t Lie: Unlocking Training‑Efficient RL Through the Model’s Own Signals
55. NeurIPS 2025Approximating Shapley Explanations in Reinforcement Learning
56. NeurIPS 2025AREAL: A Large-Scale Asynchronous Reinforcement Learning System for Language Reasoning
57. NeurIPS 2025ARIA: Training Language Agents with Intention-driven Reward Aggregation
58. NeurIPS 2025Ask a Strong LLM Judge when Your Reward Model is Uncertain
59. NeurIPS 2025Asymmetric REINFORCE for off-Policy Reinforcement Learning: Balancing positive and negative rewards
60. NeurIPS 2025AutoEdit: Automatic Hyperparameter Tuning for Image Editing
61. NeurIPS 2025Automaton Constrained Q-Learning
62. NeurIPS 2025Avoiding exp(R) scaling in RLHF through Preference-based Exploration
63. NeurIPS 2025Bayesian Ego-graph inference for Networked Multi-Agent Reinforcement Learning
64. NeurIPS 2025Behavior Injection: Preparing Language Models for Reinforcement Learning
65. NeurIPS 2025Benchmarking End-To-End Performance of AI-Based Chip Placement Algorithms
66. NeurIPS 2025Bernstein–von Mises for Adaptively Collected Data
67. NeurIPS 2025Better Estimation of the Kullback--Leibler Divergence Between Language Models
68. NeurIPS 2025Better NTK Conditioning: A Free Lunch from (ReLU) Nonlinear Activation in Wide Neural Networks
69. NeurIPS 2025Beyond Accuracy: Dissecting Mathematical Reasoning for LLMs Under Reinforcement Learning
70. NeurIPS 2025Beyond Average Value Function in Precision Medicine: Maximum Probability-Driven Reinforcement Learning for Survival Analysis
71. NeurIPS 2025Beyond Expectations: Quantile-Guided Alignment for Risk-Calibrated Language Models
72. NeurIPS 2025Beyond Least Squares: Uniform Approximation and the Hidden Cost of Misspecification
73. NeurIPS 2025Beyond Scalar Rewards: An Axiomatic Framework for Lexicographic MDPs
74. NeurIPS 2025Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning
75. NeurIPS 2025Beyond Verifiable Rewards: Scaling Reinforcement Learning in Language Models to Unverifiable Data
76. NeurIPS 2025Bi-Level Decision-Focused Causal Learning for Large-Scale Marketing Optimization: Bridging Observational and Experimental Data
77. NeurIPS 2025Bi-Level Knowledge Transfer for Multi-Task Multi-Agent Reinforcement Learning
78. NeurIPS 2025Bigger, Regularized, Categorical: High-Capacity Value Functions are Efficient Multi-Task Learners
79. NeurIPS 2025BioReason: Incentivizing Multimodal Biological Reasoning within a DNA-LLM Model
80. NeurIPS 2025Blending Complementary Memory Systems in Hybrid Quadratic-Linear Transformers
81. NeurIPS 2025Blindfolded Experts Generalize Better: Insights from Robotic Manipulation and Videogames
82. NeurIPS 2025Boosting Resilience of Large Language Models through Causality-Driven Robust Optimization
83. NeurIPS 2025Bootstrap Off-policy with World Model
84. NeurIPS 2025Boundary-to-Region Supervision for Offline Safe Reinforcement Learning
85. NeurIPS 2025BraVE: Offline Reinforcement Learning for Discrete Combinatorial Action Spaces
86. NeurIPS 2025BREAD: Branched Rollouts from Expert Anchors Bridge SFT & RL for Reasoning
87. NeurIPS 2025Breaking the Performance Ceiling in Reinforcement Learning requires Inference Strategies
88. NeurIPS 2025BridgeVLA: Input-Output Alignment for Efficient 3D Manipulation Learning with Vision-Language Models
89. NeurIPS 2025BTL-UI: Blink-Think-Link Reasoning Model for GUI Agent
90. NeurIPS 2025CAD-Coder: Text-to-CAD Generation with Chain-of-Thought and Geometric Reward
91. NeurIPS 2025Capturing Individual Human Preferences with Reward Features
92. NeurIPS 2025Causality Meets Locality: Provably Generalizable and Scalable Policy Learning for Networked Systems
93. NeurIPS 2025Centralized Reward Agent for Knowledge Sharing and Transfer in Multi-Task Reinforcement Learning
94. NeurIPS 2025Certifying Stability of Reinforcement Learning Policies using Generalized Lyapunov Functions
95. NeurIPS 2025ChartSketcher: Reasoning with Multimodal Feedback and Reflection for Chart Understanding
96. NeurIPS 2025Checklists Are Better Than Reward Models For Aligning Language Models
97. NeurIPS 2025CHPO: Constrained Hybrid-action Policy Optimization for Reinforcement Learning
98. NeurIPS 2025Classical Planning with LLM-Generated Heuristics: Challenging the State of the Art with Python Code
99. NeurIPS 2025CLAWS:Creativity detection for LLM-generated solutions using Attention Window of Sections
100. NeurIPS 2025Co-Reinforcement Learning for Unified Multimodal Understanding and Generation

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.