基础模型适配论文趋势 2023–2026

主要结论

• 基础模型适配论文从 2023 年的 159 篇增长到 2026 年的 602 篇，三年间扩大到约 3.8 倍。
• NeurIPS 是发基础模型适配论文最多的会议，2023–2026 年共 531 篇，占四个会议总量的 36%。
• 交叉方向里涨得最快的是深度学习 · foundation models：同时属于两个主题的论文从 2023 年的 7 篇增至 2026 年的 66 篇。
• 在「元学习与迁移」的 5 个主题里，它的 2026 年论文数排第 1；同组增长最快的持续学习是 1.7 倍，基础模型适配是 3.8 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 2026(Mis)generalization of Helpful-Only Fine-Tuning
• ICML 2026Active Learning with Foundation Model Priors: Efficient Learning under Class Imbalance
• ICLR 2026Benchmarking ECG Foundational Models: A Reality Check Across Clinical Tasks
• CVPR 2026CD-Buffer Complementary Dual-Buffer Framework for Test-Time Adaptation in Adverse Weather
• NeurIPS 2025An Investigation of Memorization Risk in Healthcare Foundation Models
• ICML 2025A Bayesian Model Selection Criterion for Selecting Pretraining Checkpoints
• ICLR 2025Better autoregressive regression with LLMs via regression-aware fine-tuning
• CVPR 20255%>100%: Breaking Performance Shackles of Full Fine-Tuning on Visual Recognition Tasks
• NeurIPS 2024Instruction Tuning Large Language Models to Understand Electronic Health Records
• ICML 2024By Tying Embeddings You Are Assuming the Distributional Hypothesis
• ICLR 2024A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation
• CVPR 2024DePT: Decoupled Prompt Tuning
• NeurIPS 2023A Fast and Accurate Estimator for Large Scale Linear Model via Data Averaging
• ICML 2023Are Neurons Actually Collapsed? On the Fine-Grained Structure in Neural Representations
• ICLR 2023A Closer Look at Model Adaptation using Feature Distortion and Simplicity Bias
• CVPR 2023A-La-Carte Prompt Tuning (APT): Combining Distinct Data via Composable Prompting
• NeurIPS 2026A Graph Foundation Model for Unified Clustering
• ICML 2026AdaMeZO: Adam-style Zeroth-Order Optimizer for LLM Fine-tuning Without Maintaining the Moments
• ICLR 2026Bridging Radiology and Pathology Foundation Models via Concept-Based Multimodal Co-Adaptation
• CVPR 2026Fed-ADE Adaptive Learning Rate for Federated Post-adaptation under Distribution Shift

全部基础模型适配论文

共 36 篇，第 1 / 1 页

1. ICML 2023A Kernel-Based View of Language Model Fine-Tuning
2. ICML 2023AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation
3. ICML 2023Are Neurons Actually Collapsed? On the Fine-Grained Structure in Neural Representations
4. ICML 2023Bidirectional Adaptation for Robust Semi-Supervised Learning with Inconsistent Data Distributions
5. ICML 2023ClimaX: A foundation model for weather and climate
6. ICML 2023CocktailSGD: Fine-tuning Foundation Models over 500Mbps Networks
7. ICML 2023Conditional Tree Matching for Inference-Time Adaptation of Tree Prediction Models
8. ICML 2023Constant Matters: Fine-grained Error Bound on Differentially Private Continual Observation
9. ICML 2023Cross-Modal Fine-Tuning: Align then Refine
10. ICML 2023Curious Replay for Model-based Adaptation
11. ICML 2023Double-Weighting for Covariate Shift Adaptation
12. ICML 2023Efficient Personalized Federated Learning via Sparse Model-Adaptation
13. ICML 2023Explore and Exploit the Diverse Knowledge in Model Zoo for Domain Generalization
14. ICML 2023Exploring the Benefits of Training Expert Language Models over Instruction Tuning
15. ICML 2023Flash: Concept Drift Adaptation in Federated Learning
16. ICML 2023Flexible Model Aggregation for Quantile Regression
17. ICML 2023How Many Perturbations Break This Model? Evaluating Robustness Beyond Adversarial Accuracy
18. ICML 2023Human-Timescale Adaptation in an Open-Ended Task Space
19. ICML 2023In Search for a Generalizable Method for Source Free Domain Adaptation
20. ICML 2023LegendreTron: Uprising Proper Multiclass Loss Learning
21. ICML 2023Magneto: A Foundation Transformer
22. ICML 2023Master-ASR: Achieving Multilingual Scalability and Low-Resource Adaptation in ASR with Modular Learning
23. ICML 2023MetaDiffuser: Diffusion Model as Conditional Planner for Offline Meta-RL
24. ICML 2023Mitigating Spurious Correlations in Multi-modal Models during Fine-tuning
25. ICML 2023Model Transferability with Responsive Decision Subjects
26. ICML 2023mPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video
27. ICML 2023On the Power of Foundation Models
28. ICML 2023On the Role of Attention in Prompt-tuning
29. ICML 2023Random Classification Noise does not defeat All Convex Potential Boosters Irrespective of Model Choice
30. ICML 2023RLSbench: Domain Adaptation Under Relaxed Label Shift
31. ICML 2023SinDDM: A Single Image Denoising Diffusion Model
32. ICML 2023Structural Re-weighting Improves Graph Domain Adaptation
33. ICML 2023Target-Aware Generative Augmentations for Single-Shot Adaptation
34. ICML 2023Task-Specific Skill Localization in Fine-tuned Language Models
35. ICML 2023Taxonomy-Structured Domain Adaptation
36. ICML 2023Test-time Adaptation with Slot-Centric Models

常见问题

2023–2026 年四大会议一共有多少篇基础模型适配论文？

共 1,492 篇，按年份分别是 2023 年 159 篇、2024 年 270 篇、2025 年 461 篇、2026 年 602 篇。

NeurIPS 2026 有多少篇基础模型适配论文？

NeurIPS 2026 有 182 篇基础模型适配论文，上一届是 174 篇。

ICLR 2026 有多少篇基础模型适配论文？

ICLR 2026 有 187 篇基础模型适配论文，上一届是 149 篇。

ICML 2026 有多少篇基础模型适配论文？

ICML 2026 有 142 篇基础模型适配论文，上一届是 76 篇。

CVPR 2026 有多少篇基础模型适配论文？

CVPR 2026 有 91 篇基础模型适配论文，上一届是 62 篇。

哪个会议的基础模型适配论文最多？

NeurIPS，2023–2026 年共 531 篇。