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 113 篇，第 1 / 3 页

1. NeurIPS 2026$\varphi$TD: Distributional Reinforcement Learning using Characteristic Functions
2. NeurIPS 2026$f$-GRPO & Beyond: Divergence-Based Reinforcement Learning Algorithms for General LLM Alignment
3. NeurIPS 2026A Geometric Perspective on Reward Function Updates in Inverse Reinforcement Learning
4. NeurIPS 2026A New Framework for Quantum Reinforcement Learning
5. NeurIPS 2026A Primal-dual Approach for Semi-Infinitely Constrained Reinforcement Learning
6. NeurIPS 2026Accelerating Safe Reinforcement Learning with Massive Parallelism
7. NeurIPS 2026ACQueReLlo: Alignment-Aware Constrained Quantization via Reinforcement Learning for Large Language Models
8. NeurIPS 2026Adaptive Stepsizes for Eligibility Traces in Deep Reinforcement Learning
9. NeurIPS 2026Addressing Sparse-Rewards in RL with Scalable Hierarchical Novel Eigen Options
10. NeurIPS 2026AGiR: Mitigating Gift Over-Reliance in Mixed-Motive Games
11. NeurIPS 2026AstraFlow: Dataflow-Oriented Reinforcement Learning for Agentic LLMs
12. NeurIPS 2026Behavior-Discriminative Reward Shaping for Reward-Robust Reinforcement Learning
13. NeurIPS 2026Benign Reinforcement Learning Can Amplify Latent Backdoors
14. NeurIPS 2026Conservatism Controllable Compositional Guidance for Offline Safe Reinforcement Learning
15. NeurIPS 2026Context Value Informed In-Context Reinforcement Learning
16. NeurIPS 2026Cross-Question Reliable Reinforcement Learning
17. NeurIPS 2026CS-DICE: Offline Reinforcement Learning with Coherent Occupancy Regularization
18. NeurIPS 2026CURe: Conservative Unlearning with Soft-Gating Regularization for Offline Reinforcement Learning
19. NeurIPS 2026DACA-GRPO: Denoising-Aware Credit Assignment for Reinforcement Learning in Diffusion Language Models
20. NeurIPS 2026DARLING: Detection Augmented Reinforcement Learning with Non-Stationary Guarantees
21. NeurIPS 2026Deep Double Q-learning
22. NeurIPS 2026Designing Reinforcement Learning for Diffusion Models: A Unified Path-Space View
23. NeurIPS 2026DGRAF: Observation-Quality-Aware Reinforcement Learning for Dynamic Reconfigurable Batteries
24. NeurIPS 2026Diffusion Subgoal Planning for Long-Horizon Offline Goal-Conditioned Reinforcement Learning
25. NeurIPS 2026DiReCL: Learning Differentiable Reward Code with Inverse Reinforcement Learning
26. NeurIPS 2026Distribution Corrected Decision Transformer for Offline Reinforcement Learning with Imbalanced Datasets
27. NeurIPS 2026DiversePlace: Diversity-Seeking Curriculum Reinforcement Learning for Macro Placement
28. NeurIPS 2026DORA: A Scalable Asynchronous Reinforcement Learning System for Language Model Training
29. NeurIPS 2026Drift Q-Learning
30. NeurIPS 2026DUDS: Dual-stage Data Selection for Efficient Reinforcement Learning with Verifiable Rewards
31. NeurIPS 2026Dyna-Style Safety Augmented Reinforcement Learning: Staying Safe in the Face of Uncertainty
32. NeurIPS 2026DynamAuction: a reinforcement learning environment for repeated auction with dynamic value
33. NeurIPS 2026ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning
34. NeurIPS 2026Equivariant Reinforcement Learning for Clifford Quantum Circuit Synthesis
35. NeurIPS 2026Escaping Path Mirages in Offline Goal-Conditioned Reinforcement Learning
36. NeurIPS 2026EventLens: Event-Structure Reinforcement Learning for Video Understanding
37. NeurIPS 2026Evolutionary System Prompt Learning for Reinforcement Learning in LLMs
38. NeurIPS 2026Flow Matching Reinforcement Learning via SDE Inference
39. NeurIPS 2026Focal Reward: Balanced Reinforcement Learning under Rubric-Based Rewards
40. NeurIPS 2026GDMD: Guiding Distribution Matching Distillation with Gradient-Based Reinforcement Learning
41. NeurIPS 2026Graph Topology Augmentation for Prioritized Sweeping in Non-stationary Reinforcement Learning
42. NeurIPS 2026HiFloat4 Format for End-To-End Reinforcement Learning Post-Training of Large Language Models
43. NeurIPS 2026High-Dimensional Robotic Reinforcement Learning with Developing Synergies
44. NeurIPS 2026IFDECORATOR: Wrapping Instruction Following Reinforcement Learning with Verifiable Rewards
45. NeurIPS 2026Imitation Dominates Reinforcement: Direct In-Context RL Is Closer to ICL Than RL
46. NeurIPS 2026Imperfect World Models are Exploitable
47. NeurIPS 2026Instability of Meta-Learning Intrinsic Rewards for Policy Gradient Reinforcement Learning
48. NeurIPS 2026Kernel Value Regression in Offline Reinforcement Learning
49. NeurIPS 2026Learning in Context, Guided by Choice: A Reward-Free Paradigm for Reinforcement Learning with Transformers
50. NeurIPS 2026Learning POMDP World Models from Observations with Language-Model Priors

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。