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

6,885 papers, page 46 of 138

2251. NeurIPS 2026Adaptive Inference for Functionals of M-Estimands
2252. NeurIPS 2026Adaptive Scheduling Pipeline For Multi-Instance Asynchronous Reinforcement Learning
2253. NeurIPS 2026Adaptive Stepsizes for Eligibility Traces in Deep Reinforcement Learning
2254. NeurIPS 2026Addressing Exogenous Variability in Cooperative Multi-Agent Reinforcement Learning
2255. NeurIPS 2026Addressing Sparse-Rewards in RL with Scalable Hierarchical Novel Eigen Options
2256. NeurIPS 2026Adversary-Robust Learning from Fully Asynchronous Directional Derivative Estimates
2257. NeurIPS 2026AEM: Adaptive Entropy Modulation for Multi-Turn Agentic Reinforcement Learning
2258. NeurIPS 2026AETDICE: Unified Framework and Offline Optimization for Nonlinear Multi-Objective RL
2259. NeurIPS 2026AffectGPT-RL: Revealing Roles of Reinforcement Learning in Open-Vocabulary Emotion Recognition
2260. NeurIPS 2026AgentForesight: Online Auditing for Early Failure Prediction in Multi-Agent Systems
2261. NeurIPS 2026Agentic Reward Modeling: Verifying GUI Agent via Progressive Trajectory-Grounded Interaction
2262. NeurIPS 2026Aligning Flow Map Policies with Optimal $Q$-Guidance
2263. NeurIPS 2026Alignment Dynamics in LLM Fine-Tuning
2264. NeurIPS 2026AlphaPareto: Formulaic Alpha Discovery with LLM-Guided Multi-Objective Reinforcement Learning
2265. NeurIPS 2026Amortized Molecular Optimization via Group Relative Policy Optimization
2266. NeurIPS 2026An Analytical Model of Compute-limited Multistage Training Pipelines
2267. NeurIPS 2026Angular Networks: Low-Bit Learning from Randomized Similarity Estimators
2268. NeurIPS 2026ART for Diffusion Sampling: A Reinforcement Learning Approach to Timestep Scheduling
2269. NeurIPS 2026ASTOR: Multi-Task Code Reinforcement Learning via Utility-Driven Coordination
2270. NeurIPS 2026AstraFlow: Dataflow-Oriented Reinforcement Learning for Agentic LLMs
2271. NeurIPS 2026Attention-Based Soft Answer Sets
2272. NeurIPS 2026Augmented Lagrangian Method for Last-Iterate Convergence for Constrained MDPs
2273. NeurIPS 2026AURA: An Autonomous Retouching Agent with Photographic Visual Thinking
2274. NeurIPS 2026Axiomatic Reinforcement Learning for Open Multi-Agent Systems from Shapley Axioms
2275. NeurIPS 2026Axiomatic World Modeling for Physics Reasoning
2276. NeurIPS 2026BalCapRL : A Balanced Framework for RL-Based MLLM Image Captioning
2277. NeurIPS 2026Bayesian Preference Learning for Test-Time Steerable Reward Models
2278. NeurIPS 2026BECON: Belief-Conditioned Constrained Multi-Objective Reinforcement Learning under Drifting Preferences and Budgets
2279. NeurIPS 2026Behaving Better, Thinking Worse: Sycophancy Across Post-Training Stages
2280. NeurIPS 2026Behavior Cloning is Not All You Need: The Optimality of On-Policy Distillation for Noisy Expert Feedback
2281. NeurIPS 2026Behavior-Discriminative Reward Shaping for Reward-Robust Reinforcement Learning
2282. NeurIPS 2026Behavioral Foundation Models for Quality Diversity
2283. NeurIPS 2026Bellman Residual Minimization for Control: Geometry, Stationarity, and Convergence
2284. NeurIPS 2026Benchmarking and Optimizing Multimodal Structured Generation: The OracleGraph Dataset and PRISM Framework
2285. NeurIPS 2026Benign Reinforcement Learning Can Amplify Latent Backdoors
2286. NeurIPS 2026Beyond Domains: Reusing Web Skills via Transferable Interaction Patterns
2287. NeurIPS 2026Beyond Outcome Rewards: Step-Level Self-Distilled Policy Optimization for Deep Search Agents
2288. NeurIPS 2026Beyond Prediction: Steering VLM Agents with Retrospective World Modeling
2289. NeurIPS 2026Beyond SFT-to-RL: Pre-alignment via Black-box On-policy Distillation for Multimodal RL
2290. NeurIPS 2026Beyond Success Rates: Trainability and Extractability in Offline GCRL
2291. NeurIPS 2026Beyond the Dirac Delta: Mitigating Diversity Collapse in Reinforcement Fine-Tuning for Image Generation
2292. NeurIPS 2026Beyond Training Time, Test-Time Coordination is Essential for Cooperative MARL
2293. NeurIPS 2026BiasTrojan: LLM Judgers Are Easily Distorted by Few Hundreds of Contrastive Biased Training Data
2294. NeurIPS 2026Bilevel Optimization of Synthetic Trajectories for Multi-Turn LLM Fine-Tuning
2295. NeurIPS 2026BioMicroAgents: A Co-evolutionary Multi-Agent Framework for High-Fidelity Biomicroscopy Imaging
2296. NeurIPS 2026BIRD-RL: Scaling Agentic Reinforcement Learning over Stateful Data-Centric Environments
2297. NeurIPS 2026BlendCast: Teaching Vision-Language Model to Anticipate Member Skill in Weather Ensembles
2298. NeurIPS 2026BlenderFORGE: Framework for Optimizing Reactive 3D-Graphics Editing Ability of MLLMs
2299. NeurIPS 2026Block-R1: Rethinking the Role of Block Size in Multi-domain Reinforcement Learning for Diffusion Large Language Models
2300. NeurIPS 2026Boost Reasoning Evolution via Responsive Rollout Difficulty Manipulation

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.