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papersSEP 12 04:00 UTC

Soft Prompting Approach Adapts Vision-Language Models with Few Shots

A new arXiv paper tackles few-shot object detection with vision-language models in domains that differ from their training data, such as aerial, industrial, and medical imagery, where only ten labeled images are available. Rather than optimizing discrete text prompts, the authors propose a soft prompting method for adaptation. The work is a cross-listing on arXiv cs.AI.

arXiv few-shot object detection model adaptation prompt engineering soft prompting vision-language models

COVERAGE · 2 REPORTS · LINKS GO TO THE ORIGINAL OUTLETS

arXiv cs.LGYour Model Already Knows Don't Teach It, Learn to Ask It: Soft Prompting for Few-Shot Adaptation of Vision-Language Models ↗SEP 11 04:00 UTC

arXiv cs.AIYour Model Already Knows Don't Teach It, Learn to Ask It: Soft Prompting for Few-Shot Adaptation of Vision-Language Models ↗SEP 12 04:00 UTC