Hsiao-Ying Huang

CLIP models suffer from a surprisingly strong "center bias," causing them to miss important objects outside the image's central region, even when those objects are crucial for accurate vision-language understanding.

Forget confidence scores: a modality-aware early exit strategy for spoken language models slashes decoding costs without sacrificing accuracy or perceptual quality, revealing that speech tokens require specialized handling compared to text.