3 papers
cs.LG2026
Towards Understanding Feature Learning in Parameter Transfer
Hua Yuan, Xuran Meng, Qiufeng Wang +6
Parameter transfer is a central paradigm in transfer learning, enabling knowledge reuse across tasks and domains by sharing model parameters between upstream and downstream models.…
cs.CV2025
Extracting Multimodal Learngene in CLIP: Unveiling the Multimodal Generalizable Knowledge
Ruiming Chen, Junming Yang, Shiyu Xia +3
CLIP (Contrastive Language-Image Pre-training) has attracted widespread attention for its multimodal generalizable knowledge, which is significant for downstream tasks. However, th…
cs.LG2025
STHFL: Spatio-Temporal Heterogeneous Federated Learning
Shunxin Guo, Hongsong Wang, Shuxia Lin +2
Federated learning is a new framework that protects data privacy and allows multiple devices to cooperate in training machine learning models. Previous studies have proposed multip…