Huang-Xun Chen

From Knowing to Abstaining: Bridging the Representation-Action Gap in Vision-Language Models

The ability of vision-language models (VLMs) to abstain from unanswerable questions is as important as their ability to answer answerable ones accurately. Recently, several benchmarks have emerged to evaluate and improve VLM abstention, but they have substantial limitations. First, samples often contain shortcut cues i...