Paper recorded by Signals 4 on 2026-10-09 in cs.LG. Abstract reproduced from arXiv; link to the original below.
Published 2026-10-09 on arXiv · recorded by Signals 4 on 2026-10-12
Category: cs.LG · 机器学习 · first seen 2026-10-12
In clinical practice, experts often begin by converting raw inputs into a set of expert features before making a decision. While black-box models trained on raw input can outperform models trained on expert views, it remains unclear what predictive signal the raw model exploits beyond what the expert view captures. We introduce an audit framework to quantify this gap using Shared Canonical Compone