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 4 / 4 页

151. CVPR 2023Learning Dynamic Style Kernels for Artistic Style Transfer
152. CVPR 2023Manipulating Transfer Learning for Property Inference
153. CVPR 2023Modernizing Old Photos Using Multiple References via Photorealistic Style Transfer
154. CVPR 2023Neural Preset for Color Style Transfer
155. CVPR 2023QuantArt: Quantizing Image Style Transfer Towards High Visual Fidelity
156. CVPR 2023Representation Learning for Visual Object Tracking by Masked Appearance Transfer
157. CVPR 2023Semantic Human Parsing via Scalable Semantic Transfer Over Multiple Label Domains
158. CVPR 2023StyleRF: Zero-Shot 3D Style Transfer of Neural Radiance Fields
159. CVPR 2023T-SEA: Transfer-Based Self-Ensemble Attack on Object Detection
160. CVPR 2023Transfer Knowledge From Head to Tail: Uncertainty Calibration Under Long-Tailed Distribution
161. CVPR 2023Visual Language Pretrained Multiple Instance Zero-Shot Transfer for Histopathology Images
162. CVPR 2023Visual Prompt Tuning for Generative Transfer Learning
163. CVPR 2023Zero-Shot Pose Transfer for Unrigged Stylized 3D Characters
164. ICLR 2023Decompose to Generalize: Species-Generalized Animal Pose Estimation
165. ICLR 2023Is Forgetting Less a Good Inductive Bias for Forward Transfer?
166. ICLR 2023Meta-Evolve: Continuous Robot Evolution for One-to-many Policy Transfer
167. ICLR 2023Multitask Prompt Tuning Enables Parameter-Efficient Transfer Learning
168. ICLR 2023Provable Sim-to-real Transfer in Continuous Domain with Partial Observations
169. ICLR 2023Revisit Finetuning strategy for Few-Shot Learning to Transfer the Emdeddings
170. ICLR 2023Teacher Guided Training: An Efficient Framework for Knowledge Transfer
171. ICLR 2023Transfer Learning with Deep Tabular Models
172. ICLR 2023Transfer NAS with Meta-learned Bayesian Surrogates
173. ICML 2023Hypothesis Transfer Learning with Surrogate Classification Losses: Generalization Bounds through Algorithmic Stability
174. ICML 2023Which Invariance Should We Transfer? A Causal Minimax Learning Approach
175. NeurIPS 2023Combining Behaviors with the Successor Features Keyboard
176. NeurIPS 2023Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference
177. NeurIPS 2023Data-Centric Learning from Unlabeled Graphs with Diffusion Model
178. NeurIPS 2023Diffused Redundancy in Pre-trained Representations
179. NeurIPS 2023Does progress on ImageNet transfer to real-world datasets?
180. NeurIPS 2023Doubly Robust Augmented Transfer for Meta-Reinforcement Learning
181. NeurIPS 2023Easy Bayesian Transfer Learning with Informative Priors
182. NeurIPS 2023Enhancing Knowledge Transfer for Task Incremental Learning with Data-free Subnetwork
183. NeurIPS 2023Fast Trainable Projection for Robust Fine-tuning
184. NeurIPS 2023ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning
185. NeurIPS 2023Graph-Structured Gaussian Processes for Transferable Graph Learning
186. NeurIPS 2023Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data
187. NeurIPS 2023LART: Neural Correspondence Learning with Latent Regularization Transformer for 3D Motion Transfer
188. NeurIPS 2023LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning
189. NeurIPS 2023Make the U in UDA Matter: Invariant Consistency Learning for Unsupervised Domain Adaptation
190. NeurIPS 2023ReContrast: Domain-Specific Anomaly Detection via Contrastive Reconstruction
191. NeurIPS 2023Robust Knowledge Transfer in Tiered Reinforcement Learning
192. NeurIPS 2023Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning
193. NeurIPS 2023To Stay or Not to Stay in the Pre-train Basin: Insights on Ensembling in Transfer Learning
194. NeurIPS 2023Transfer Learning with Affine Model Transformation
195. NeurIPS 2023Transportability for Bandits with Data from Different Environments
196. NeurIPS 2023URL: A Representation Learning Benchmark for Transferable Uncertainty Estimates
197. NeurIPS 2023VPGTrans: Transfer Visual Prompt Generator across LLMs

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。