Silin Cheng

VaMP: Variational Multi-Modal Prompt Learning for Vision-Language Models

Vision-language models (VLMs), such as CLIP, have shown strong generalization under zero-shot settings, yet adapting them to downstream tasks with limited supervision remains a significant challenge. Existing multi-modal prompt learning methods typically rely on fixed, shared prompts and determinist…