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 197 篇，第 3 / 4 页

101. CVPR 2024Geometry Transfer for Stylizing Radiance Fields
102. CVPR 2024Initialization Matters for Adversarial Transfer Learning
103. CVPR 2024Model Inversion Robustness: Can Transfer Learning Help?
104. CVPR 2024NeRF Analogies: Example-Based Visual Attribute Transfer for NeRFs
105. CVPR 2024Robust Synthetic-to-Real Transfer for Stereo Matching
106. CVPR 2024Structured Model Probing: Empowering Efficient Transfer Learning by Structured Regularization
107. CVPR 2024Style Injection in Diffusion: A Training-free Approach for Adapting Large-scale Diffusion Models for Style Transfer
108. CVPR 2024Towards Robust 3D Pose Transfer with Adversarial Learning
109. CVPR 2024Transfer CLIP for Generalizable Image Denoising
110. ICLR 2024Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling
111. ICLR 2024Geometrically Aligned Transfer Encoder for Inductive Transfer in Regression Tasks
112. ICLR 2024Principled Architecture-aware Scaling of Hyperparameters
113. ICLR 2024Seeking Neural Nuggets: Knowledge Transfer in Large Language Models from a Parametric Perspective
114. ICLR 2024Tight Rates in Supervised Outlier Transfer Learning
115. ICLR 2024Zero-Shot Continuous Prompt Transfer: Generalizing Task Semantics Across Language Models
116. ICML 2024A Universal Transfer Theorem for Convex Optimization Algorithms Using Inexact First-order Oracles
117. ICML 2024Adaptive Group Personalization for Federated Mutual Transfer Learning
118. ICML 2024Adversarially Robust Hypothesis Transfer Learning
119. ICML 2024Bridging Data Gaps in Diffusion Models with Adversarial Noise-Based Transfer Learning
120. ICML 2024EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs
121. ICML 2024Federated Continual Learning via Prompt-based Dual Knowledge Transfer
122. ICML 2024Learning Modality Knowledge Alignment for Cross-Modality Transfer
123. ICML 2024Let Go of Your Labels with Unsupervised Transfer
124. ICML 2024On Hypothesis Transfer Learning of Functional Linear Models
125. ICML 2024Smoothness Adaptive Hypothesis Transfer Learning
126. ICML 2024State-Free Inference of State-Space Models: The *Transfer Function* Approach
127. ICML 2024When is Transfer Learning Possible?
128. NeurIPS 2024Learning Transferable Features for Implicit Neural Representations
129. NeurIPS 2024Model-Based Transfer Learning for Contextual Reinforcement Learning
130. NeurIPS 2024On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift
131. NeurIPS 2024On the Surprising Effectiveness of Attention Transfer for Vision Transformers
132. NeurIPS 2024Revealing Distribution Discrepancy by Sampling Transfer in Unlabeled Data
133. NeurIPS 2024SHMT: Self-supervised Hierarchical Makeup Transfer via Latent Diffusion Models
134. NeurIPS 2024SubjECTive-QA: Measuring Subjectivity in Earnings Call Transcripts' QA Through Six-Dimensional Feature Analysis
135. NeurIPS 2024The Impact of Geometric Complexity on Neural Collapse in Transfer Learning
136. NeurIPS 2024The Limits of Transfer Reinforcement Learning with Latent Low-rank Structure
137. NeurIPS 2024Transfer Learning for Diffusion Models
138. NeurIPS 2024Transfer Learning for Latent Variable Network Models
139. NeurIPS 2024Transfer Learning with Informative Priors: Simple Baselines Better than Previously Reported
140. NeurIPS 2024Transfer Q-star : Principled Decoding for LLM Alignment
141. NeurIPS 2024Universality in Transfer Learning for Linear Models
142. CVPR 2023A Data-Based Perspective on Transfer Learning
143. CVPR 2023BlackVIP: Black-Box Visual Prompting for Robust Transfer Learning
144. CVPR 2023CAP-VSTNet: Content Affinity Preserved Versatile Style Transfer
145. CVPR 2023Class Attention Transfer Based Knowledge Distillation
146. CVPR 2023DKT: Diverse Knowledge Transfer Transformer for Class Incremental Learning
147. CVPR 2023ERM-KTP: Knowledge-Level Machine Unlearning via Knowledge Transfer
148. CVPR 2023Few-Shot Semantic Image Synthesis With Class Affinity Transfer
149. CVPR 2023Inversion-Based Style Transfer With Diffusion Models
150. CVPR 2023JAWS: Just a Wild Shot for Cinematic Transfer in Neural Radiance Fields

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。