2 papers
cs.CV2023
CLIP-KD: An Empirical Study of CLIP Model Distillation
Chuanguang Yang, Zhulin An, Libo Huang +5
Contrastive Language-Image Pre-training (CLIP) has become a promising language-supervised visual pre-training framework. This paper aims to distill small CLIP models supervised by…
cs.CL2023
UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation
Daixuan Cheng, Shaohan Huang, Junyu Bi +7
Large Language Models (LLMs) are popular for their impressive abilities, but the need for model-specific fine-tuning or task-specific prompt engineering can hinder their generaliza…