通用机器学习 · reinforcement learning论文趋势 2023–2026

主要结论

• 通用机器学习 · reinforcement learning论文从 2023 年的 287 篇增长到 2026 年的 575 篇，三年间扩大到约 2.0 倍。
• ICLR 是发通用机器学习 · reinforcement learning论文最多的会议，2023–2026 年共 847 篇，占四个会议总量的 51%。
• 交叉方向里涨得最快的是扩散模型：同时属于两个主题的论文从 2023 年的 2 篇增至 2026 年的 34 篇。
• 在「通用机器学习」的 6 个主题里，它的 2026 年论文数排第 2；同组增长最快的通用机器学习 · evaluation是 4.3 倍，通用机器学习 · reinforcement learning是 2.0 倍。

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

• NeurIPS 2026The Sample Complexity of Multiple Change Point Identification under Bandit Feedback
• ICML 2026De-attribute to Forget for LLM Unlearning
• ICLR 2026AbstRaL: Augmenting LLMs' Reasoning by Reinforcing Abstract Thinking
• CVPR 2026Dynamic Important Example Mining for Reinforcement Finetuning
• NeurIPS 2025RULE: Reinforcement UnLEarning Achieves Forget-retain Pareto Optimality
• ICML 2025The Number of Trials Matters in Infinite-Horizon General-Utility Markov Decision Processes
• ICLR 2025A General Framework for Off-Policy Learning with Partially-Observed Reward
• CVPR 2025Automated Proof of Polynomial Inequalities via Reinforcement Learning
• NeurIPS 2024Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm
• ICML 2024Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation
• ICLR 2024Bandits with Replenishable Knapsacks: the Best of both Worlds
• CVPR 2024Improving Unsupervised Hierarchical Representation with Reinforcement Learning
• NeurIPS 2023General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence
• ICML 2023Non-stationary Reinforcement Learning under General Function Approximation
• ICLR 2023A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning
• CVPR 2023Frustratingly Easy Regularization on Representation Can Boost Deep Reinforcement Learning
• NeurIPS 2026Learning When to Stop: Selective Imitation Learning Under Arbitrary Dynamics Shift
• ICML 2026Fox in the Henhouse: Supply-Chain Backdoor Attacks Against Reinforcement Learning
• ICLR 2026APPLE: Toward General Active Perception via Reinforcement Learning
• CVPR 2026Reinforcement-Guided Synthetic Data Generation for Privacy-Sensitive Identity Recognition

全部通用机器学习 · reinforcement learning论文

共 335 篇，第 6 / 7 页

251. ICLR 2026Rethinking Policy Diversity in Ensemble Policy Gradient in Large-Scale Reinforcement Learning
252. ICLR 2026Revisiting Matrix Sketching in Linear Bandits: Achieving Sublinear Regret via Dyadic Block Sketching
253. ICLR 2026Revolutionizing Reinforcement Learning Framework for Diffusion Large Language Models
254. ICLR 2026Reward Is Enough: LLMs Are In-Context Reinforcement Learners
255. ICLR 2026Rewarding Doubt: A Reinforcement Learning Approach to Calibrated Confidence Expression of Large Language Models
256. ICLR 2026Risk-Sensitive Reinforcement Learning for Alleviating Exploration Dilemmas in Large Language Models
257. ICLR 2026RiskPO: Risk-based Policy Optimization with Verifiable Reward for LLM Post-Training
258. ICLR 2026RL of Thoughts: Navigating LLM Reasoning with Inference-time Reinforcement Learning
259. ICLR 2026RLVER: Reinforcement Learning with Verifiable Emotion Rewards for Empathetic Agents
260. ICLR 2026Robust Adaptive Multi-Step Predictive Shielding
261. ICLR 2026Robustness in the Face of Partial Identifiability in Reward Learning
262. ICLR 2026SAC Flow: Sample-Efficient Reinforcement Learning of Flow-Based Policies via Velocity-Reparameterized Sequential Modeling
263. ICLR 2026Safe Continuous-time Multi-Agent Reinforcement Learning via Epigraph Form
264. ICLR 2026Safe Exploration via Policy Priors
265. ICLR 2026SafeMPO: Constrained Reinforcement Learning with Probabilistic Incremental Improvement
266. ICLR 2026Sample Efficient Offline RL via T-Symmetry Enforced Latent State-Stitching
267. ICLR 2026Sample More to Think Less: Group Filtered Policy Optimization for Concise Reasoning
268. ICLR 2026Sample-efficient and Scalable Exploration in Continuous-Time RL
269. ICLR 2026Sample-Efficient Distributionally Robust Multi-Agent Reinforcement Learning via Online Interaction
270. ICLR 2026Scalable Exploration for High-Dimensional Continuous Control via Value-Guided Flow
271. ICLR 2026Scalable In-Context Q-Learning
272. ICLR 2026Scalable Offline Model-Based RL with Action Chunks
273. ICLR 2026Scaling Goal-conditioned Reinforcement Learning with Multistep Quasimetric Distances
274. ICLR 2026SCRIBES: Web-Scale Script-Based Semi-Structured Data Extraction with Reinforcement Learning
275. ICLR 2026Self-Aligned Reward: Towards Effective and Efficient Reasoners
276. ICLR 2026Self-Improving Skill Learning for Robust Skill-based Meta-Reinforcement Learning
277. ICLR 2026Self-Predictive Representations for Combinatorial Generalization in Behavioral Cloning
278. ICLR 2026SHAPO: Sharpness-Aware Policy Optimization for Safe Exploration
279. ICLR 2026SimpleTIR: End-to-End Reinforcement Learning for Multi-Turn Tool-Integrated Reasoning
280. ICLR 2026Simplicial Embeddings Improve Sample Efficiency in Actor–Critic Agents
281. ICLR 2026Skill Learning via Policy Diversity Yields Identifiable Representations for Reinforcement Learning
282. ICLR 2026Solving Football by Exploiting Equilibrium Structure of 2p0s Differential Games with One-Sided Information
283. ICLR 2026Solving General-Utility Markov Decision Processes in the Single-Trial Regime with Online Planning
284. ICLR 2026Solving Parameter-Robust Avoid Problems with Unknown Feasibility using Reinforcement Learning
285. ICLR 2026SPACeR: Self-Play Anchoring with Centralized Reference Models
286. ICLR 2026Sparse but Critical: A Token-Level Analysis of Distributional Shifts in RLVR Fine-Tuning of LLMs
287. ICLR 2026Spectral Bellman Method: Unifying Representation and Exploration in RL
288. ICLR 2026SPELL: Self-Play Reinforcement Learning for Evolving Long-Context Language Models
289. ICLR 2026SSVPO: Effective Step-Level Credit Assignment for RL Training of Language Models
290. ICLR 2026Stackelberg Coupling of Online Representation Learning and Reinforcement Learning
291. ICLR 2026Stackelberg Learning from Human Feedback: Preference Optimization as a Sequential Game
292. ICLR 2026STAIRS-Former: Spatio-Temporal Attention with Interleaved Recursive Structure TransFormer for Offline Mulit-task Multi-agent Reinforcement Learning
293. ICLR 2026Statistical Guarantees for Offline Domain Randomization
294. ICLR 2026Stop Unnecessary Reflection: Training LRMs for Efficient Reasoning with Adaptive Reflection and Length Coordinated Penalty
295. ICLR 2026Strict Subgoal Execution: Reliable Long-Horizon Planning in Hierarchical Reinforcement Learning
296. ICLR 2026Structured Reasoning for LLMs: A Unified Framework for Efficiency and Explainability
297. ICLR 2026SUSD: Structured Unsupervised Skill Discovery through State Factorization
298. ICLR 2026Tackling Heavy-Tailed Q-Value Bias in Offline-to-Online Reinforcement Learning with Laplace-Robust Modeling
299. ICLR 2026Task Tokens: A Flexible Approach to Adapting Behavior Foundation Models
300. ICLR 2026TD-JEPA: Latent-predictive Representations for Zero-Shot Reinforcement Learning

常见问题

2023–2026 年四大会议一共有多少篇通用机器学习 · reinforcement learning论文？

共 1,676 篇，按年份分别是 2023 年 287 篇、2024 年 403 篇、2025 年 411 篇、2026 年 575 篇。

NeurIPS 2026 有多少篇通用机器学习 · reinforcement learning论文？

NeurIPS 2026 有 113 篇通用机器学习 · reinforcement learning论文，上一届是 108 篇。

ICLR 2026 有多少篇通用机器学习 · reinforcement learning论文？

ICLR 2026 有 335 篇通用机器学习 · reinforcement learning论文，上一届是 230 篇。

ICML 2026 有多少篇通用机器学习 · reinforcement learning论文？

ICML 2026 有 113 篇通用机器学习 · reinforcement learning论文，上一届是 71 篇。

CVPR 2026 有多少篇通用机器学习 · reinforcement learning论文？

CVPR 2026 有 14 篇通用机器学习 · reinforcement learning论文，上一届是 2 篇。

哪个会议的通用机器学习 · reinforcement learning论文最多？

ICLR，2023–2026 年共 847 篇。