8 citations · 11 across the 4 of their papers we have counts for
4 papers
Personalize Anything for Free with Diffusion Transformer
Haoran Feng, Zehuan Huang, Lin Li +2
Personalized image generation aims to produce images of user-specified concepts while enabling flexible editing. Recent training-free approaches, while exhibit higher computational…
Federated Learning with Classifier Shift for Class Imbalance
Yunheng Shen, Haoxiang Wang, Hairong Lv
Federated learning aims to learn a global model collaboratively while the training data belongs to different clients and is not allowed to be exchanged. However, the statistical he…
Learning to Decompose Visual Features with Latent Textual Prompts
Feng Wang, Manling Li, Xudong Lin +3
Recent advances in pre-training vision-language models like CLIP have shown great potential in learning transferable visual representations. Nonetheless, for downstream inference,…
Boost Neural Networks by Checkpoints
Feng Wang, Guoyizhe Wei, Qiao Liu +3
Training multiple deep neural networks (DNNs) and averaging their outputs is a simple way to improve the predictive performance. Nevertheless, the multiplied training cost prevents…