公共政策分析论文趋势 2023–2026

主要结论

• 公共政策分析论文从 2023 年的 16 篇增长到 2026 年的 29 篇，三年间扩大到约 1.8 倍。
• NeurIPS 是发公共政策分析论文最多的会议，2023–2026 年共 45 篇，占四个会议总量的 54%。
• 交叉方向里涨得最快的是强化学习：同时属于两个主题的论文从 2023 年的 6 篇增至 2026 年的 18 篇。
• 在「社会公益」的 5 个主题里，它的 2026 年论文数排第 2；同组增长最快的电网优化是 2.6 倍，公共政策分析是 1.8 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 2026Co-Evolving Policy Distillation
• ICML 2026Partial Identification of Policy Values under Network Interference
• ICLR 2026Joint Selection for Large-Scale Pre-Training Data via Policy Gradient-based Mask Learning
• CVPR 2026Real-Time Long Horizon Air Quality Forecasting via Group-Relative Policy Optimization
• NeurIPS 2025Real-Time Hyper-Personalized Generative AI Should Be Regulated to Prevent the Rise of "Digital Heroin"
• ICML 2025Improving Value Estimation Critically Enhances Vanilla Policy Gradient
• CVPR 2025AffordDP: Generalizable Diffusion Policy with Transferable Affordance
• NeurIPS 2024SafeWorld: Geo-Diverse Safety Alignment
• ICML 2024Optimal Differentially Private Model Training with Public Data
• NeurIPS 2023Creating a Public Repository for Joining Private Data
• ICML 2023Exponential Smoothing for Off-Policy Learning
• ICLR 2023Linear Convergence of Natural Policy Gradient Methods with Log-Linear Policies
• NeurIPS 2026Distributionally-Robust Policy Learning from Observational Data
• ICML 2026Personalized Policy Learning through Discrete Experimentation
• NeurIPS 2025$\textit{Hyper-GoalNet}$: Goal-Conditioned Manipulation Policy Learning with HyperNetworks
• ICML 2025Theoretical guarantees on the best-of-n alignment policy
• NeurIPS 2024Improved off-policy training of diffusion samplers
• ICML 2024Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining
• NeurIPS 2023Global Optimality and Finite Sample Analysis of Softmax Off-Policy Actor Critic under State Distribution Mismatch
• ICML 2023On Many-Actions Policy Gradient

全部公共政策分析论文

共 29 篇，第 1 / 1 页

1. CVPR 2026Real-Time Long Horizon Air Quality Forecasting via Group-Relative Policy Optimization
2. ICLR 2026Joint Selection for Large-Scale Pre-Training Data via Policy Gradient-based Mask Learning
3. ICML 2026Partial Identification of Policy Values under Network Interference
4. ICML 2026Personalized Policy Learning through Discrete Experimentation
5. ICML 2026Recurrent Structural Policy Gradient for Partially Observable Mean Field Games
6. ICML 2026Reusing Trajectories in Policy Gradients Enables Fast Convergence
7. ICML 2026Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data
8. NeurIPS 2026Beyond SFT-to-RL: Pre-alignment via Black-box On-policy Distillation for Multimodal RL
9. NeurIPS 2026Boosting Off-Policy RLVR with Data-Centric Replay
10. NeurIPS 2026Co-Evolving Policy Distillation
11. NeurIPS 2026Compose Your Oracles: Off Policy Improvement with Aggregated Guidance
12. NeurIPS 2026Cornerstones or Stumbling Blocks? Deciphering the Rock Tokens in On-Policy Distillation
13. NeurIPS 2026Distributionally-Robust Policy Learning from Observational Data
14. NeurIPS 2026Don’t Let Gains FADE: Breaking Down Policy Gradient Weights in RL
15. NeurIPS 2026Feedback World Model Enables Precise Guidance of Diffusion Policy
16. NeurIPS 2026FLAG: Flow Policy MaxEnt-RL by Latent Augmented Guidance
17. NeurIPS 2026Global linear convergence of entropy-regularized softmax policy gradient beyond tabular MDPs
18. NeurIPS 2026Jump Start Your Policy Learning with Lessons from 145,000 Training Runs
19. NeurIPS 2026Learning Multimodal One-step Flow Policy via Value-weighted Optimal Transport
20. NeurIPS 2026METAFORGET: Audit-Driven Update-Policy Learning for Reliable Language Model Unlearning
21. NeurIPS 2026Off-policy Learning with Excursion Policies
22. NeurIPS 2026Policy Gradient Algorithms in Average-Reward Multichain MDPs
23. NeurIPS 2026Policy Regret Minimization in Partially Observable Markov Games
24. NeurIPS 2026Proposing Better Rollouts for On-Policy Distillation
25. NeurIPS 2026Reverse to Advance: Teleoperation-Cost Effective Hard Policy Learning from Reversed Easy Tasks
26. NeurIPS 2026Selective Off-Policy Reference Tuning with Plan Guidance
27. NeurIPS 2026The AI Observatory: A Public Measure of Real-World AI Use
28. NeurIPS 2026Trust Region Policy Distillation
29. NeurIPS 2026Your Teacher Can’t Help You Here: Combating Supervision Fidelity Decay in On-Policy Distillation

常见问题

2023–2026 年四大会议一共有多少篇公共政策分析论文？

共 84 篇，按年份分别是 2023 年 16 篇、2024 年 21 篇、2025 年 18 篇、2026 年 29 篇。

NeurIPS 2026 有多少篇公共政策分析论文？

NeurIPS 2026 有 22 篇公共政策分析论文，上一届是 11 篇。

ICLR 2026 有多少篇公共政策分析论文？

ICLR 2026 有 1 篇公共政策分析论文。

ICML 2026 有多少篇公共政策分析论文？

ICML 2026 有 5 篇公共政策分析论文，上一届是 6 篇。

CVPR 2026 有多少篇公共政策分析论文？

CVPR 2026 有 1 篇公共政策分析论文，上一届是 1 篇。

哪个会议的公共政策分析论文最多？

NeurIPS，2023–2026 年共 45 篇。