Zi-Kang Wang

Bi-CoG: Bi-Consistency-Guided Self-Training for Vision-Language Models

Exploiting unlabeled data through semi-supervised learning (SSL) or leveraging pre-trained models via fine-tuning are two prevailing paradigms for addressing label-scarce scenarios. Recently, growing attention has been given to combining fine-tuning of pre-trained vision-language models (VLMs) with