深度学习 · transfer learning论文趋势 2023–2026

主要结论

• 深度学习 · transfer learning论文从 2023 年的 56 篇降到 2026 年的 54 篇，热度在回落。
• NeurIPS 是发深度学习 · transfer learning论文最多的会议，2023–2026 年共 71 篇，占四个会议总量的 36%。
• 交叉方向里涨得最快的是多模态大模型：同时属于两个主题的论文从 2023 年的 2 篇增至 2026 年的 5 篇。
• 在「深度学习」的 11 个主题里，它的 2026 年论文数排第 11；同组增长最快的扩散模型是 4.1 倍，深度学习 · transfer learning是 1.0 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 2026Emergent Misalignment as Data-Mediated Transfer
• ICML 2026Transfer Learning in High-dimensional Ising Models
• ICLR 2026TiTok: Transfer Token-level Knowledge via Contrastive Excess to Transplant LoRA
• CVPR 2026Unlocking Positive Transfer in Incrementally Learning Surgical Instruments A Self-reflection
• NeurIPS 2025Asymmetric Duos: Sidekicks Improve Uncertainty
• ICML 2025An Improved Clique-Picking Algorithm for Counting Markov Equivalent DAGs via Super Cliques Transfer
• ICLR 2025GraphBridge: Towards Arbitrary Transfer Learning in GNNs
• CVPR 2025A4A: Adapter for Adapter Transfer via All-for-All Mapping for Cross-Architecture Models
• NeurIPS 2024Transfer Learning with Informative Priors: Simple Baselines Better than Previously Reported
• ICML 2024Adversarially Robust Hypothesis Transfer Learning
• ICLR 2024Geometrically Aligned Transfer Encoder for Inductive Transfer in Regression Tasks
• CVPR 2024Geometry Transfer for Stylizing Radiance Fields
• NeurIPS 2023Diffused Redundancy in Pre-trained Representations
• ICML 2023Hypothesis Transfer Learning with Surrogate Classification Losses: Generalization Bounds through Algorithmic Stability
• ICLR 2023Transfer Learning with Deep Tabular Models
• CVPR 2023A Data-Based Perspective on Transfer Learning
• NeurIPS 2026Learning Rate Transfer for Hybrid Transformer-SSM Architectures
• ICML 2026Transfer Learning in Nonparametric Regression with Deep ReLU Networks
• ICLR 2026Detect, Decide, Unlearn: A Transfer-Aware Framework for Continual Learning
• CVPR 2026Nonlinear Color Transfer via Learnable Bezier Flows

全部深度学习 · transfer learning论文

共 37 篇，第 1 / 1 页

1. ICML 2026Conformal Calibration Transfer
2. ICML 2026Geometric Embedding Alignment via Curvature Matching in Transfer Learning
3. ICML 2026Hierarchical Successor Representation for Robust Transfer
4. ICML 2026Hyperparameter Transfer with Mixture-of-Expert Layers
5. ICML 2026Large Language Model Teaches Visual Students: Cross-Modality Transfer of Fine-Grained Conceptual Knowledge
6. ICML 2026Protein Language Model Embeddings Improve Generalization of Implicit Transfer Operators
7. ICML 2026SMAC: Score-Matched Actor-Critics for Robust Offline-to-Online Transfer
8. ICML 2026Stable Localized Conformal Prediction via Transduction
9. ICML 2026The Geometry of Sequential Learning: Lie-Bracket Prediction of Transfer Order
10. ICML 2026Train Once, Reuse Everywhere: Generalizable Implicit ICL by Routing Attention
11. ICML 2026Transfer Learning in High-dimensional Ising Models
12. ICML 2026Transfer Learning in Nonparametric Regression with Deep ReLU Networks
13. ICML 2026What Makes a Strong Model? A Unified Spectral Analysis of Knowledge Transfer over High-dimensional Linear Regression
14. ICML 2025An Improved Clique-Picking Algorithm for Counting Markov Equivalent DAGs via Super Cliques Transfer
15. ICML 2025Do Multiple Instance Learning Models Transfer?
16. ICML 2025Features are fate: a theory of transfer learning in high-dimensional regression
17. ICML 2025Function Encoders: A Principled Approach to Transfer Learning in Hilbert Spaces
18. ICML 2025Function-Space Learning Rates
19. ICML 2025Lightspeed Geometric Dataset Distance via Sliced Optimal Transport
20. ICML 2025On the Provable Separation of Scales in Maximal Update Parameterization
21. ICML 2025Overtrained Language Models Are Harder to Fine-Tune
22. ICML 2025Predicting mutational effects on protein binding from folding energy
23. ICML 2025TLLC: Transfer Learning-based Label Completion for Crowdsourcing
24. ICML 2024A Universal Transfer Theorem for Convex Optimization Algorithms Using Inexact First-order Oracles
25. ICML 2024Adaptive Group Personalization for Federated Mutual Transfer Learning
26. ICML 2024Adversarially Robust Hypothesis Transfer Learning
27. ICML 2024Bridging Data Gaps in Diffusion Models with Adversarial Noise-Based Transfer Learning
28. ICML 2024EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs
29. ICML 2024Federated Continual Learning via Prompt-based Dual Knowledge Transfer
30. ICML 2024Learning Modality Knowledge Alignment for Cross-Modality Transfer
31. ICML 2024Let Go of Your Labels with Unsupervised Transfer
32. ICML 2024On Hypothesis Transfer Learning of Functional Linear Models
33. ICML 2024Smoothness Adaptive Hypothesis Transfer Learning
34. ICML 2024State-Free Inference of State-Space Models: The *Transfer Function* Approach
35. ICML 2024When is Transfer Learning Possible?
36. ICML 2023Hypothesis Transfer Learning with Surrogate Classification Losses: Generalization Bounds through Algorithmic Stability
37. ICML 2023Which Invariance Should We Transfer? A Causal Minimax Learning Approach

常见问题

2023–2026 年四大会议一共有多少篇深度学习 · transfer learning论文？

共 197 篇，按年份分别是 2023 年 56 篇、2024 年 44 篇、2025 年 43 篇、2026 年 54 篇。

NeurIPS 2026 有多少篇深度学习 · transfer learning论文？

NeurIPS 2026 有 18 篇深度学习 · transfer learning论文，上一届是 16 篇。

ICLR 2026 有多少篇深度学习 · transfer learning论文？

ICLR 2026 有 9 篇深度学习 · transfer learning论文，上一届是 9 篇。

ICML 2026 有多少篇深度学习 · transfer learning论文？

ICML 2026 有 13 篇深度学习 · transfer learning论文，上一届是 10 篇。

CVPR 2026 有多少篇深度学习 · transfer learning论文？

CVPR 2026 有 14 篇深度学习 · transfer learning论文，上一届是 8 篇。

哪个会议的深度学习 · transfer learning论文最多？

NeurIPS，2023–2026 年共 71 篇。