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 45 of 138

2201. ICML 2026ViSurf: Visual Supervised-and-Reinforcement Fine-Tuning for Large Vision-and-Language Models
2202. ICML 2026Vulnerable Agent Identification in Large-Scale Multi-Agent Reinforcement Learning
2203. ICML 2026Well-Posed KL-Regularized Control via Wasserstein and Kalman–Wasserstein KL Divergences
2204. ICML 2026What Does Flow-Matching Bring to TD-Learning?
2205. ICML 2026What Does Vision Tool-Use Reinforcement Learning Really Learn? Disentangling Tool-Induced and Intrinsic Effects for Crop-and-Zoom
2206. ICML 2026What Makes Value Learning Efficient in Residual Reinforcement Learning?
2207. ICML 2026What Reward Structure Enables Efficient Sparse-Reward RL? A Proof-of-Concept with Policy-Aware Matrix Completion
2208. ICML 2026What You Think is What You See: Driving Exploration in VLM Agents via Visual-Linguistic Curiosity
2209. ICML 2026When Can You Poison Rewards? A Tight Characterization of Reward Poisoning in Linear MDPs
2210. ICML 2026When Does Predictive Inverse Dynamics Outperform Behavior Cloning?
2211. ICML 2026When RL Meets Adaptive Speculative Training: A Unified Training-Serving System
2212. ICML 2026When Simple Problems Wear Complex Costumes: Improving Efficiency in LRM's Adaptive Reasoning
2213. ICML 2026When to Memorize and When to Stop: Gated Recurrent Memory for Long-Context Reasoning
2214. ICML 2026Which Heads Matter for Reasoning? RL-Guided KV Cache Compression
2215. ICML 2026Why Dedicated Critics: Eliminating Target Drift in Multi-Constraint RL
2216. ICML 2026Why Linear Recurrent Memory Works in Partially Observable Reinforcement Learning
2217. ICML 2026Why Tree-Style Branching Matters for Thought Advantage Estimation in GRPO
2218. ICML 2026World Models in Pieces: Structural Certification of General Agents
2219. ICML 2026World-R1: Reinforcing 3D Constraints for Text-to-Video Generation
2220. ICML 2026WorldCompass: Reinforcement Learning for Long-Horizon World Models
2221. ICML 2026WS-GRPO: Weakly-Supervised Group-Relative Policy Optimization for Rollout-Efficient Reasoning
2222. ICML 2026XRPO: Pushing the Limits of GRPO with Targeted Exploration and Exploitation
2223. ICML 2026You Can Learn Tokenization End-to-End with Reinforcement Learning
2224. ICML 2026Zero-Shot Off-Policy Learning
2225. ICML 2026Zero-source LLM Hallucination Detection with Human-like Criteria Probing
2226. NeurIPS 2026\texttt{FEROM}: Frontier Endogenous Reveal-Order Marginal Policy Optimization for Masked Diffusion LMs
2227. NeurIPS 2026$\gamma$-weakly $\theta$-up-concavity: A Unified Framework for Non-Convex Optimization Beyond DR-Submodular and OSS Functions
2228. NeurIPS 2026$\varphi$TD: Distributional Reinforcement Learning using Characteristic Functions
2229. NeurIPS 2026$f$-GRPO & Beyond: Divergence-Based Reinforcement Learning Algorithms for General LLM Alignment
2230. NeurIPS 2026$R^2E$: A Role-driven Reward Evolutionary Framework for Automated Reward Function Design
2231. NeurIPS 20262-Step Agent: How a Bayesian Decision Maker Learns from AI-Decision Support
2232. NeurIPS 2026A Computational Perspective to Data Ablation Experiments
2233. NeurIPS 2026A Constrained Bi-level Optimization Framework for Constrained Preference-Based Reinforcement Learning
2234. NeurIPS 2026A Few Teacher Steps Go a Long Way: Cost-Efficient On-Policy Data Augmentation for Agent Post-Training
2235. NeurIPS 2026A Geometric Perspective on Reward Function Updates in Inverse Reinforcement Learning
2236. NeurIPS 2026A latent control model for realistic rodent motion
2237. NeurIPS 2026A Model of Diverse Sampling from Language Models
2238. NeurIPS 2026A New Framework for Quantum Reinforcement Learning
2239. NeurIPS 2026A Primal-dual Approach for Semi-Infinitely Constrained Reinforcement Learning
2240. NeurIPS 2026A Systematic Evaluation of Co-folding Model Representations for Small-Molecule Learning
2241. NeurIPS 2026A$^2$IQL: Adaptive Asymmetric Implicit Q Learning for Automated Warehouse Consolidation
2242. NeurIPS 2026AbFlowNet: Optimizing Antibody-Antigen Binding Energy via Diffusion-GFlowNet Fusion
2243. NeurIPS 2026Absolute State-wise Constrained Policy Optimization: High-Probability State-wise Constraints Satisfaction
2244. NeurIPS 2026Accelerating Safe Reinforcement Learning with Massive Parallelism
2245. NeurIPS 2026ACQueReLlo: Alignment-Aware Constrained Quantization via Reinforcement Learning for Large Language Models
2246. NeurIPS 2026Actor-Accelerated Policy Dual Averaging for Reinforcement Learning in Continuous Action Spaces
2247. NeurIPS 2026Ad-Hoc Teamwork from Human Demonstrations
2248. NeurIPS 2026AdaptFlow: State-Anchored Goal Conditioning with Flow Matching for Offline Goal-Conditioned RL
2249. NeurIPS 2026Adaptive and Neutral Theory of Evolution Strategies for Large Language Models
2250. NeurIPS 2026Adaptive Communication Range for Scalable Cooperative Multi-Agent 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.