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

1,021 papers, page 6 of 21

251. ICML 2026Dreaming in Code for Curriculum Learning in Open-Ended Worlds
252. ICML 2026DRIFT: Decoupled Rollouts and Importance-Weighted Fine-Tuning for Efficient Multi-Turn Optimization
253. ICML 2026DRIVE: Best Data Scheduling Practices for Reinforcement Learning with Verifiable Reward in Competitive Code Generation
254. ICML 2026DRIVE: Distributional and Retrieval-Augmented Bidding with Value Evaluation
255. ICML 2026DRL-STAF: A Deep Reinforcement Learning Framework for State-Aware Forecasting of Complex Multivariate Hidden Markov Processes
256. ICML 2026dTRPO : Trajectory Reduction in Policy Optimization of Diffusion Large Language Models
257. ICML 2026DualCOIL: Offline Imitation Learning from Contrasting Demonstrations
258. ICML 2026DyGRO-VLA: Cross-Task Scaling of Vision–Language–Action Models via Dynamic Grouped Residual Optimization
259. ICML 2026Dynamic Optimizations of LLM Ensembles with Two-Stage Reinforcement Learning Agents
260. ICML 2026Dynamic Programming for Epistemic Uncertainty in Markov Decision Processes
261. ICML 2026Dynamics Are Learned, Not Told: Semi-Supervised Discovery of Latent Dynamics Geometries For Zero-Shot Policy Adaptation
262. ICML 2026EAPO: Enhancing Policy Optimization with On-Demand Expert Assistance
263. ICML 2026EARL: Towards a Unified Analysis-Guided Reinforcement Learning Framework for Egocentric Interaction Reasoning and Pixel Grounding
264. ICML 2026ECG-R1: Protocol-Guided and Modality-Agnostic MLLM for Reliable ECG Interpretation
265. ICML 2026ECHO: Entropy-Confidence Hybrid Optimization for Test-Time Reinforcement Learning
266. ICML 2026EchoRL: Reinforcement Learning via Rollout Echoing
267. ICML 2026EDCO: Dynamic Curriculum Orchestration for Domain-specific Large Language Model Fine-tuning
268. ICML 2026EEmo-Logic: A Unified Dataset and Multi-Stage Framework for Comprehensive Image-Evoked Emotion Assessment
269. ICML 2026Effects of Structural Reward Shaping on Biophysical Properties in RL-Trained Plasmid Generators
270. ICML 2026Efficient and Safe Molecular Assembly via Reinforcement Learning and Constraint Solving
271. ICML 2026Efficient and Uncertainty-Aware Diffusion Framework for Offline-to-Online Reinforcement Learning
272. ICML 2026Efficient Preference Poisoning Attack on Offline RLHF
273. ICML 2026Efficient, Property-Aligned Fan-Out Retrieval via RL-Compiled Diffusion
274. ICML 2026Efficiently Solving Discounted MDPs via Predictions with Unknown Prediction Errors
275. ICML 2026Ego3S: Select, Strengthen, and Synchronize for Efficient Egocentric Reasoning
276. ICML 2026Elign: Equivariant Diffusion Model Alignment from Foundational Machine Learned Force Fields
277. ICML 2026Embedding-perturbed Exploration Preference Optimization for Flow Models
278. ICML 2026Emergence of Exploration in Policy Gradient Reinforcement Learning via Retrying
279. ICML 2026Emergent Communication Under Misinformation
280. ICML 2026Enhancing Multi-Modal LLMs Reasoning via Difficulty-Aware Group Normalization
281. ICML 2026Enhancing Reasoning for Diffusion LLMs via Distribution Matching Policy Optimization
282. ICML 2026Entropy-Aware On-Policy Distillation of Language Models
283. ICML 2026Episodic Memory-Guided Controllable Experience Synthesis for Reinforcement Learning
284. ICML 2026Epistemic Gain, Aleatoric Cost: Uncertainty Decomposition in Multi-Agent Debate for Math Reasoning
285. ICML 2026Error Amplification Limits ANN-to-SNN Conversion in Continuous Control
286. ICML 2026Escaping the Likelihood Trap: Geometric Diversity Optimization for Long-Form Image Captioning
287. ICML 2026Escaping the Mode: Multi-Answer Reinforcement Learning in LMs
288. ICML 2026Escaping the Verifier: Learning to Reason via Demonstrations
289. ICML 2026Estimation of Treatment Effects Under Nonstationarity via the Truncated Policy Gradient Estimator
290. ICML 2026ETS: Energy-Guided Test-Time Scaling for Training-Free RL Alignment
291. ICML 2026Evaluating and Rewarding LALMs for Expressive Role-Play TTS via Mean Continuation Log-Probability
292. ICML 2026Evaluating Parameter Efficient Methods for RLVR
293. ICML 2026Evolution Strategies at Scale: LLM Fine-Tuning Beyond Reinforcement Learning
294. ICML 2026Evolution Strategies at the Hyperscale
295. ICML 2026EVOLVING ROLLOUTS: Harnessing Historical Experience for Web Agent Evolution in Reinforcement Learning
296. ICML 2026Exact Unlearning in Reinforcement Learning
297. ICML 2026Expanding the Capabilities of Reinforcement Learning via Text Feedback
298. ICML 2026Expected Return Causes Outcome-Level Mode Collapse in Reinforcement Learning and How to Fix It with Inverse Probability Scaling
299. ICML 2026Expected Returns and Policy Inconsistency-Aware Offline Federated Deep Reinforcement Learning
300. ICML 2026Experience Augmented Policy Optimization for LLM Reasoning

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.