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

1,827 papers, page 6 of 37

251. ICLR 2026Expertise Can Be Helpful for Reinforcement Learning-based Macro Placement
252. ICLR 2026Exploration vs Exploitation: Rethinking RLVR through Clipping, Entropy, and Spurious Reward
253. ICLR 2026Exploratory Diffusion Model for Unsupervised Reinforcement Learning
254. ICLR 2026Exploratory Memory-Augmented LLM Agent via Hybrid On- and Off-Policy Optimization
255. ICLR 2026Explore-on-Graph: Incentivizing Autonomous Exploration of Large Language Models on Knowledge Graphs with Path-refined Reward Modeling
256. ICLR 2026EXPO: Stable Reinforcement Learning with Expressive Policies
257. ICLR 2026Fair Policy Aggregation from Standard Policy Optimization
258. ICLR 2026FAPO: Flawed-Aware Policy Optimization for Efficient and Reliable Reasoning
259. ICLR 2026FastGRPO: Accelerating Policy Optimization via Concurrency-aware Speculative Decoding and Online Draft Learning
260. ICLR 2026Fathom-DeepResearch: Unlocking Long Horizon Information Retrieval and Synthesis for SLMs
261. ICLR 2026Federated ADMM from Bayesian Duality
262. ICLR 2026Fine-R1: Make Multi-modal LLMs Excel in Fine-Grained Visual Recognition by Chain-of-Thought Reasoning
263. ICLR 2026Fine-tuning Behavioral Cloning Policies with Preference‑Based Reinforcement Learning
264. ICLR 2026Fine-Tuning Diffusion Models via Intermediate Distribution Shaping
265. ICLR 2026Finite-Time Analysis of Actor-Critic Methods with Deep Neural Network Approximation
266. ICLR 2026FIRE: Frobenius-Isometry Reinitialization for Balancing the Stability–Plasticity Tradeoff
267. ICLR 2026floq: Training Critics via Flow-Matching for Scaling Compute in Value-Based RL
268. ICLR 2026Flow Actor-Critic for Offline Reinforcement Learning
269. ICLR 2026Flow Matching Policy Gradients
270. ICLR 2026Flow Matching with Injected Noise for Offline-to-Online Reinforcement Learning
271. ICLR 2026Flow-Based Single-Step Completion for Efficient and Expressive Policy Learning
272. ICLR 2026Flowing Through States: Neural ODE Regularization for Reinforcement Learning
273. ICLR 2026FlowRL: Matching Reward Distributions for LLM Reasoning
274. ICLR 2026Foundational Automatic Evaluators: Scaling Multi-Task Generative Evaluator Training for Reasoning-Centric Domains
275. ICLR 2026FrameThinker: Learning to Think with Long Videos via Multi-Turn Frame Spotlighting
276. ICLR 2026From Broad Exploration to Stable Synthesis: Entropy-Guided Optimization for Autoregressive Image Generation
277. ICLR 2026From Curiosity to Caution: Mitigating Reward Hacking for Best-of-$N$ with Pessimism
278. ICLR 2026From f(x) and g(x) to f(g(x)): LLMs Learn New Skills in RL by Composing Old Ones
279. ICLR 2026From Gradient Volume to Shapley Fairness: Towards Fair Multi-Task Learning
280. ICLR 2026From Language to Locomotion: Retargeting-free Humanoid Control via Motion Latent Guidance
281. ICLR 2026From Narrow to Panoramic Vision: Attention-Guided Cold-Start Reshapes Multimodal Reasoning
282. ICLR 2026From Observations to Events: Event-Aware World Models for Reinforcement Learning
283. ICLR 2026From Parameters to Behaviors: Unsupervised Compression of the Policy Space
284. ICLR 2026From Seeing to Experiencing: Scaling Navigation Foundation Models with Reinforcement Learning
285. ICLR 2026From Sequential to Parallel: Reformulating Dynamic Programming as GPU Kernels for Large-Scale Stochastic Combinatorial Optimization
286. ICLR 2026From Sorting Algorithms to Scalable Kernels: Bayesian Optimization in High-Dimensional Permutation Spaces
287. ICLR 2026From Ticks to Flows: Dynamics of Neural Reinforcement Learning in Continuous Environments
288. ICLR 2026From Verifiable Dot to Reward Chain: Harnessing Verifiable Reference-based Rewards for Reinforcement Learning of Open-ended Generation
289. ICLR 2026Frozen Policy Iteration: Computationally Efficient RL under Linear $Q^{\pi}$ Realizability for Deterministic Dynamics
290. ICLR 2026FrugalRAG: Less is More in RL Finetuning for Multi-hop Question Answering
291. ICLR 2026Gaia2: Benchmarking LLM Agents on Dynamic and Asynchronous Environments
292. ICLR 2026GALAX: Graph-Augmented Language Model for Explainable Reinforcement-Guided Subgraph Reasoning in Precision Medicine
293. ICLR 2026GAR: Generative Adversarial Reinforcement Learning for Formal Theorem Proving
294. ICLR 2026GAS: Enhancing Reward-Cost Balance of Generative Model-assisted Offline Safe RL
295. ICLR 2026GDPval: Evaluating AI Model Performance on Real-World Economically Valuable Tasks
296. ICLR 2026GEM: A Gym for Generalist LLMs
297. ICLR 2026General Exploratory Bonus for Optimistic Exploration in RLHF
298. ICLR 2026Generalizable End-to-End Tool-Use RL with Synthetic CodeGym
299. ICLR 2026Generalization of RLVR Using Causal Reasoning as a Testbed
300. ICLR 2026Generalized Parallel Scaling with Interdependent Generations

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.