Yiming Wang

SAM3's "segment anything" promise falls short in pathology, revealing a significant gap between its prompt-based usage and task-trained performance for medical image segmentation.

Unleashing LLMs' reasoning powers on speech unlocks a new ASR paradigm, slashing error rates by up to 17% simply by having the model "think" before transcribing.