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

2,079 papers, page 5 of 42

201. ICML 2026Decision-focused Sparse Tangent Portfolio Optimization
202. ICML 2026DECOR: Learning to Decompose and Collaborate in Deep Search via Multi-Agent Reinforcement Learning
203. ICML 2026Decoupled Training with Local Reinforcement Fine-Tuning in Federated Learning
204. ICML 2026Decoupling Reasoning and Confidence: Resurrecting Calibration in Reinforcement Learning from Verifiable Rewards
205. ICML 2026Decoupling Skeleton and Flesh: Efficient Multimodal Table Reasoning with Disentangled Alignment and Structure-aware Guidance
206. ICML 2026Deep Flow Networks
207. ICML 2026Deep Reinforcement Learning Finds Bayes-Nash Equilibrium in Competitive Newsvendor Problems
208. ICML 2026DeepHA: Scaling Action Chains Elicits Deep Hierarchical Agents
209. ICML 2026DeFacto: Counterfactual Thinking with Images for Enforcing Evidence-Grounded and Faithful Reasoning
210. ICML 2026Demystifying Entropy Control in LLM RL Training: Theoretical Analysis and Dynamic Scheduling
211. ICML 2026Depth-Breadth Synergy in RLVR: Unlocking LLM Reasoning Gains with Adaptive Exploration
212. ICML 2026Designing Observation and Action Models for Efficient Reinforcement Learning with LLMs
213. ICML 2026Deterministic Inference across Tensor Parallel Sizes That Eliminates Training-Inference Mismatch
214. ICML 2026DexMachina: Functional Retargeting for Bimanual Dexterous Manipulation
215. ICML 2026DF-ExpEnse: Diffusion Filtered Exploration for Sample Efficient Finetuning
216. ICML 2026Differentiable Weightless Controllers: Learning Logic Circuits for Continuous Control
217. ICML 2026Differential Smoothing Mitigates Sharpening and Improves LLM Reasoning
218. ICML 2026Diffusing to Coordinate: Efficient Online Multi-Agent Diffusion Policies
219. ICML 2026Diffusion Controller: Framework, Algorithms and Parameterization
220. ICML 2026Direct Flow Q-Learning
221. ICML 2026Directly Optimizing Natural Language Explanations for Behavioral Faithfulness: Simulatability and Recoverability
222. ICML 2026Discounted Beta–Bernoulli Reward Estimation for Sample-Efficient Reinforcement Learning with Verifiable Rewards
223. ICML 2026Discrete Tilt Matching
224. ICML 2026DisPPO: Quantile-Based Distributional Reinforcement Learning for Large Language Models
225. ICML 2026Dissecting Post-Training: Uncovering the Complementary Roles of SFT and RL for Document Parsing
226. ICML 2026DistFlow: A Fully Distributed RL Framework for Scalable and Efficient LLM Post-Training
227. ICML 2026Distillation Models are Good Samplers for Diffusion Reinforcement Learning
228. ICML 2026Distinguishing Imitation Error from Intrinsic Motion Learning Difficulty
229. ICML 2026Distortion of AI Alignment Revisited: RLHF is a Decent Utilitarian Aligner
230. ICML 2026Distributed Direct Preference Optimization
231. ICML 2026Distributional Active Inference
232. ICML 2026Distributional Inverse Reinforcement Learning
233. ICML 2026Distributionally Robust Reinforcement Learning from Human Feedback
234. ICML 2026DIVA: Harnessing the Representation Divergence in Unified Multimodal Models for Mutual Reinforcement
235. ICML 2026Diversity-Driven Offline Multi-Objective Optimization via Nested Pareto Set Learning
236. ICML 2026DLM: Unified Decision Language Model for Offline Multi-Agent Sequential Decision Making
237. ICML 2026Do We Need Adam? Surprisingly Strong and Sparse Reinforcement Learning with SGD in LLMs
238. ICML 2026Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of LLM Reasoning
239. ICML 2026Does Your Reasoning Model Implicitly Know When to Stop Thinking?
240. ICML 2026Don't Overthink with Pixels: Efficient Reasoning for Segmentation
241. ICML 2026Don't Walk the Line: Boundary Guidance for Filtered Generation
242. ICML 2026Doubly Regularized Markov Decision Processes for Robust Reinforcement Learning
243. ICML 2026Doubly Robust Distributionally Robust Offline Contextual Pricing
244. ICML 2026DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research
245. ICML 2026DR-MMSearchAgent: Deepening Reasoning in Multimodal Search Agents
246. ICML 2026Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations
247. ICML 2026DR$^2$Seg: Decomposed Two-Stage Rollouts for Efficient Reasoning Segmentation in Multimodal Large Language Models
248. ICML 2026Draft-and-Audit Reinforcement Learning for Optimization Modeling
249. ICML 2026Dream-MPC: Gradient-Based Model Predictive Control with Latent Imagination
250. ICML 2026DREAM-R: Multimodal Speculative Reasoning with RL-Based Refined Drafting, Precise Verification, and Fully Parallel Execution

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.