Can Vision Language Models Learn from Visual Demonstrations of Ambiguous Spatial Reasoning?

• Published in: arXiv.org
• Main Authors: Bowen, Zhao, Leo Parker Dirac, Varshavskaya, Paulina
• Format: Paper
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 25.09.2024
• Subjects: Computer vision; Context; Learning; Visual tasks

Large vision-language models (VLMs) have become state-of-the-art for many computer vision tasks, with in-context learning (ICL) as a popular adaptation strategy for new ones. But can VLMs learn novel concepts purely from visual demonstrations, or are they limited to adapting to the output format of...