2025
LLM-empowered Dynamic Prompt Routing for Vision-Language Models Tuning under Long-Tailed Distributions
EMNLP 2025
Pre-trained vision-language models (VLMs), such as CLIP, have demonstrated impressive capability in visual tasks, but their fine-tuning often suffers from bias in class-imbalanced scenes. Recent works have introduced large language models (LLMs) to enhance VLM fine-tuning withsupplementaryy semantic