Search Results for author:
Found 3 papers, 0 papers with code
Piccolo2: General Text Embedding with Multi-task Hybrid Loss Training
In this report, we introduce Piccolo2, an embedding model that surpasses other models in the comprehensive evaluation over 6 tasks on CMTEB benchmark, setting a new state-of-the-art.
GLaMa: Joint Spatial and Frequency Loss for General Image Inpainting
Our proposed GLaMa can better capture different types of missing information by using more types of masks.
One to Transfer All: A Universal Transfer Framework for Vision Foundation Model with Few Data
Transferring with few data in a general way to thousands of downstream tasks is becoming a trend of the foundation model's application.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
