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 2 of 50

51. NeurIPS 2026BalCapRL : A Balanced Framework for RL-Based MLLM Image Captioning
52. NeurIPS 2026Bayesian Preference Learning for Test-Time Steerable Reward Models
53. NeurIPS 2026BECON: Belief-Conditioned Constrained Multi-Objective Reinforcement Learning under Drifting Preferences and Budgets
54. NeurIPS 2026Behaving Better, Thinking Worse: Sycophancy Across Post-Training Stages
55. NeurIPS 2026Behavior Cloning is Not All You Need: The Optimality of On-Policy Distillation for Noisy Expert Feedback
56. NeurIPS 2026Behavior-Discriminative Reward Shaping for Reward-Robust Reinforcement Learning
57. NeurIPS 2026Behavioral Foundation Models for Quality Diversity
58. NeurIPS 2026Bellman Residual Minimization for Control: Geometry, Stationarity, and Convergence
59. NeurIPS 2026Benchmarking and Optimizing Multimodal Structured Generation: The OracleGraph Dataset and PRISM Framework
60. NeurIPS 2026Benign Reinforcement Learning Can Amplify Latent Backdoors
61. NeurIPS 2026Beyond Domains: Reusing Web Skills via Transferable Interaction Patterns
62. NeurIPS 2026Beyond Outcome Rewards: Step-Level Self-Distilled Policy Optimization for Deep Search Agents
63. NeurIPS 2026Beyond Prediction: Steering VLM Agents with Retrospective World Modeling
64. NeurIPS 2026Beyond SFT-to-RL: Pre-alignment via Black-box On-policy Distillation for Multimodal RL
65. NeurIPS 2026Beyond Success Rates: Trainability and Extractability in Offline GCRL
66. NeurIPS 2026Beyond the Dirac Delta: Mitigating Diversity Collapse in Reinforcement Fine-Tuning for Image Generation
67. NeurIPS 2026Beyond Training Time, Test-Time Coordination is Essential for Cooperative MARL
68. NeurIPS 2026BiasTrojan: LLM Judgers Are Easily Distorted by Few Hundreds of Contrastive Biased Training Data
69. NeurIPS 2026Bilevel Optimization of Synthetic Trajectories for Multi-Turn LLM Fine-Tuning
70. NeurIPS 2026BioMicroAgents: A Co-evolutionary Multi-Agent Framework for High-Fidelity Biomicroscopy Imaging
71. NeurIPS 2026BIRD-RL: Scaling Agentic Reinforcement Learning over Stateful Data-Centric Environments
72. NeurIPS 2026BlendCast: Teaching Vision-Language Model to Anticipate Member Skill in Weather Ensembles
73. NeurIPS 2026BlenderFORGE: Framework for Optimizing Reactive 3D-Graphics Editing Ability of MLLMs
74. NeurIPS 2026Block-R1: Rethinking the Role of Block Size in Multi-domain Reinforcement Learning for Diffusion Large Language Models
75. NeurIPS 2026Boost Reasoning Evolution via Responsive Rollout Difficulty Manipulation
76. NeurIPS 2026Boosting LLM Reasoning via Human-Inspired Reward Shaping
77. NeurIPS 2026Boosting Off-Policy RLVR with Data-Centric Replay
78. NeurIPS 2026Bootstrapped Bipartite Actor-Critic for Diffusion RL
79. NeurIPS 2026Breaking the Bias Barrier in Concave Multi-Objective Reinforcement Learning
80. NeurIPS 2026Breaking the Grid: Distance-Guided Reinforcement Learning in Large Discrete Action Spaces
81. NeurIPS 2026Breaking the Second Barrier: Sub-Second Timestamped Omni-Modal Captioning
82. NeurIPS 2026Bridging Risk Approximation Gaps in Model Predictive Task Sampling via In-Context Modeling
83. NeurIPS 2026Bridging Textual Profiles and Latent User Embeddings for Personalization
84. NeurIPS 2026BSO: Safety Alignment Is Density Ratio Matching
85. NeurIPS 2026Budgeting Discretion: Theory and Evidence on Street-Level Decision-Making
86. NeurIPS 2026C2G-BENCH: A Cyber-Physical Evaluation Benchmark for Hierarchical Reinforcement Learning in Grid-Interactive Hyperscale Data Centers
87. NeurIPS 2026CaC: Advancing Video Reward Models via Hierarchical Spatiotemporal Concentrating
88. NeurIPS 2026CAFE: Causally-Guided Automated Feature Engineering with Multi-Agent Reinforcement Learning
89. NeurIPS 2026Calibrated Safe Policy Improvement for Continuous Offline Reinforcement Learning
90. NeurIPS 2026Calibrated Target Noise Recovers Curvature from the Gradients
91. NeurIPS 2026Can Folding Models Tell Binders from Bluffers? Evidence from POISK: The Patent-Derived Antibody Dataset
92. NeurIPS 2026CARD: Internalizing Expert Critique into Reinforcement Learning for Deep Search
93. NeurIPS 2026CasePlay: Self-Play Reinforcement Learning from Case Reports for Medical Reasoning
94. NeurIPS 2026Causal-Geo: Neuro-Symbolic Spatial Grounding for Situated Agent Planning
95. NeurIPS 2026Certified Policy Optimisation for Nested Causal Bandits via PAC-Bayes Risk
96. NeurIPS 2026CHAIN: Continual Heterogeneous Cooperation with Information Bottleneck for Multi-Agent Reinforcement Learning
97. NeurIPS 2026CI4A: Semantic Component Interfaces for Agents Empowering Web Automation
98. NeurIPS 2026CIG: Exploration via Conditional Information Gain
99. NeurIPS 2026Clarification as Supervision: Reinforcement Learning for Vision-Language Interfaces
100. NeurIPS 2026Clean-Label Poisoning for Gradient-Boosted Decision Trees

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.