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 847 篇，第 1 / 17 页

1. ICLR 2026$\alpha$-DPO: Robust Preference Alignment for Diffusion Models via $\alpha$ Divergence
2. ICLR 20263D-aware Disentangled Representation for Compositional Reinforcement Learning
3. ICLR 2026A Primer on SO(3) Action Representations in Deep Reinforcement Learning
4. ICLR 2026A Reward-Free Viewpoint on Multi-Objective Reinforcement Learning
5. ICLR 2026A Simple "Motivation" Can Enhance Reinforcement Finetuning of Large Reasoning Models
6. ICLR 2026AbstRaL: Augmenting LLMs' Reasoning by Reinforcing Abstract Thinking
7. ICLR 2026Accelerated Learning with Linear Temporal Logic using Differentiable Simulation
8. ICLR 2026Accelerating Diffusion Planners in Offline RL via Reward-Aware Consistency Trajectory Distillation
9. ICLR 2026Action-Free Offline-To-Online RL via Discretised State Policies
10. ICLR 2026Ada-Diffuser: Latent-Aware Adaptive Diffusion for Decision-Making
11. ICLR 2026Adaptive Rollout Allocation for Online Reinforcement Learning with Verifiable Rewards
12. ICLR 2026Adaptive Scaling of Policy Constraints for Offline Reinforcement Learning
13. ICLR 2026ADM-v2: Pursuing Full-Horizon Roll-out in Dynamics Models for Offline Policy Learning and Evaluation
14. ICLR 2026AesCoder: Code Aesthetics with Agentic Reward Feedback
15. ICLR 2026Agentic Reinforcement Learning with Implicit Step Rewards
16. ICLR 2026AgentPO: Enhancing Multi-Agent Collaboration via Reinforcement Learning
17. ICLR 2026All Roads Lead to Likelihood: The Value of Reinforcement Learning in Fine-Tuning
18. ICLR 2026AMPED: Adaptive Multi-objective Projection for balancing Exploration and skill Diversification
19. ICLR 2026Analysis of approximate linear programming solution to Markov decision problem with log barrier function
20. ICLR 2026APC-RL: Exceeding data-driven behavior priors with adaptive policy composition
21. ICLR 2026APPLE: Toward General Active Perception via Reinforcement Learning
22. ICLR 2026ARES: Multimodal Adaptive Reasoning via Difficulty-Aware Token-Level Entropy Shaping
23. ICLR 2026ARM-FM: Automated Reward Machines via Foundation Models for Compositional Reinforcement Learning
24. ICLR 2026Asynchronous Policy Gradient Aggregation for Efficient Distributed Reinforcement Learning
25. ICLR 2026ATPO: ADAPTIVE TREE POLICY OPTIMIZATION FOR MULTI-TURN MEDICAL DIALOGUE
26. ICLR 2026Attention as a Compass: Efficient Exploration for Process-Supervised RL in Reasoning Models
27. ICLR 2026Automating the Refinement of Reinforcement Learning Specifications
28. ICLR 2026AutoQD: Automatic Discovery of Diverse Behaviors with Quality-Diversity Optimization
29. ICLR 2026AutoTool: Automatic Scaling of Tool-Use Capabilities in RL via Decoupled Entropy Constraints
30. ICLR 2026Bayes Adaptive Monte Carlo Tree Search for Offline Model-based Reinforcement Learning
31. ICLR 2026Bayesian Ensemble for Sequential Decision-Making
32. ICLR 2026Bayesian Robust Cooperative Multi-Agent Reinforcement Learning Against Unknown Adversaries
33. ICLR 2026Belief-Based Offline Reinforcement Learning for Delay-Robust Policy Optimization
34. ICLR 2026Beyond Distributions: Geometric Action Control for Continuous Reinforcement Learning
35. ICLR 2026Beyond Markovian: Reflective Exploration via Bayes-Adaptive RL for LLM Reasoning
36. ICLR 2026Beyond Noisy-TVs: Noise-Robust Exploration Via Learning Progress Monitoring
37. ICLR 2026Beyond Penalization: Diffusion-based Out-of-Distribution Detection and Selective Regularization in Offline Reinforcement Learning
38. ICLR 2026Beyond Softmax and Entropy: Convergence Rates of Policy Gradients with $\boldsymbol{f}$-SoftArgmax Parameterization $\&$ Coupled Regularization
39. ICLR 2026Breaking Barriers: Do Reinforcement Fine-tuning Gains Transfer To Unseen Domains?
40. ICLR 2026Breaking Safety Paradox with Feasible Dual Policy Iteration
41. ICLR 2026Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set
42. ICLR 2026BRIDGE: Bi-level Reinforcement Learning for Dynamic Group Structure in Coalition Formation Games
43. ICLR 2026Bridging Successor Measure and Online Policy Learning with Flow Matching-Based Representations
44. ICLR 2026Bridging the performance-gap between target-free and target-based reinforcement learning
45. ICLR 2026CapRL: Stimulating Dense Image Caption Capabilities via Reinforcement Learning
46. ICLR 2026Causal Imitation Learning under Expert-Observable and Expert-Unobservable Confounding
47. ICLR 2026CDE: Curiosity-Driven Exploration for Efficient Reinforcement Learning in Large Language Models
48. ICLR 2026CE-Nav: Flow-Guided Reinforcement Refinement for Cross-Embodiment Local Navigation
49. ICLR 2026Chunking the Critic: A Transformer-based Soft Actor-Critic with N-Step Returns
50. ICLR 2026Code Driven Planning with Domain-Adaptive Selector

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。