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 56 篇，第 1 / 2 页

1. CVPR 2023A Data-Based Perspective on Transfer Learning
2. CVPR 2023BlackVIP: Black-Box Visual Prompting for Robust Transfer Learning
3. CVPR 2023CAP-VSTNet: Content Affinity Preserved Versatile Style Transfer
4. CVPR 2023Class Attention Transfer Based Knowledge Distillation
5. CVPR 2023DKT: Diverse Knowledge Transfer Transformer for Class Incremental Learning
6. CVPR 2023ERM-KTP: Knowledge-Level Machine Unlearning via Knowledge Transfer
7. CVPR 2023Few-Shot Semantic Image Synthesis With Class Affinity Transfer
8. CVPR 2023Inversion-Based Style Transfer With Diffusion Models
9. CVPR 2023JAWS: Just a Wild Shot for Cinematic Transfer in Neural Radiance Fields
10. CVPR 2023Learning Dynamic Style Kernels for Artistic Style Transfer
11. CVPR 2023Manipulating Transfer Learning for Property Inference
12. CVPR 2023Modernizing Old Photos Using Multiple References via Photorealistic Style Transfer
13. CVPR 2023Neural Preset for Color Style Transfer
14. CVPR 2023QuantArt: Quantizing Image Style Transfer Towards High Visual Fidelity
15. CVPR 2023Representation Learning for Visual Object Tracking by Masked Appearance Transfer
16. CVPR 2023Semantic Human Parsing via Scalable Semantic Transfer Over Multiple Label Domains
17. CVPR 2023StyleRF: Zero-Shot 3D Style Transfer of Neural Radiance Fields
18. CVPR 2023T-SEA: Transfer-Based Self-Ensemble Attack on Object Detection
19. CVPR 2023Transfer Knowledge From Head to Tail: Uncertainty Calibration Under Long-Tailed Distribution
20. CVPR 2023Visual Language Pretrained Multiple Instance Zero-Shot Transfer for Histopathology Images
21. CVPR 2023Visual Prompt Tuning for Generative Transfer Learning
22. CVPR 2023Zero-Shot Pose Transfer for Unrigged Stylized 3D Characters
23. ICLR 2023Decompose to Generalize: Species-Generalized Animal Pose Estimation
24. ICLR 2023Is Forgetting Less a Good Inductive Bias for Forward Transfer?
25. ICLR 2023Meta-Evolve: Continuous Robot Evolution for One-to-many Policy Transfer
26. ICLR 2023Multitask Prompt Tuning Enables Parameter-Efficient Transfer Learning
27. ICLR 2023Provable Sim-to-real Transfer in Continuous Domain with Partial Observations
28. ICLR 2023Revisit Finetuning strategy for Few-Shot Learning to Transfer the Emdeddings
29. ICLR 2023Teacher Guided Training: An Efficient Framework for Knowledge Transfer
30. ICLR 2023Transfer Learning with Deep Tabular Models
31. ICLR 2023Transfer NAS with Meta-learned Bayesian Surrogates
32. ICML 2023Hypothesis Transfer Learning with Surrogate Classification Losses: Generalization Bounds through Algorithmic Stability
33. ICML 2023Which Invariance Should We Transfer? A Causal Minimax Learning Approach
34. NeurIPS 2023Combining Behaviors with the Successor Features Keyboard
35. NeurIPS 2023Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference
36. NeurIPS 2023Data-Centric Learning from Unlabeled Graphs with Diffusion Model
37. NeurIPS 2023Diffused Redundancy in Pre-trained Representations
38. NeurIPS 2023Does progress on ImageNet transfer to real-world datasets?
39. NeurIPS 2023Doubly Robust Augmented Transfer for Meta-Reinforcement Learning
40. NeurIPS 2023Easy Bayesian Transfer Learning with Informative Priors
41. NeurIPS 2023Enhancing Knowledge Transfer for Task Incremental Learning with Data-free Subnetwork
42. NeurIPS 2023Fast Trainable Projection for Robust Fine-tuning
43. NeurIPS 2023ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning
44. NeurIPS 2023Graph-Structured Gaussian Processes for Transferable Graph Learning
45. NeurIPS 2023Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data
46. NeurIPS 2023LART: Neural Correspondence Learning with Latent Regularization Transformer for 3D Motion Transfer
47. NeurIPS 2023LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning
48. NeurIPS 2023Make the U in UDA Matter: Invariant Consistency Learning for Unsupervised Domain Adaptation
49. NeurIPS 2023ReContrast: Domain-Specific Anomaly Detection via Contrastive Reconstruction
50. NeurIPS 2023Robust Knowledge Transfer in Tiered Reinforcement Learning

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。