From the 1 of 2 linked papers with an AI index.
2 papers
cs.LG2026
ECG-InterpBench: Benchmarking the Interpretability of ECG Foundation Models with Matched-Scale Sparse Autoencoders
Yixuan Duan, Wei Qiu
The paper introduces ECG-InterpBench, a benchmark that uses matched-capacity sparse autoencoders to assess how interpretable the internal representations of frozen ECG foundation m…
cs.AI2026
CADENCE: A Cardiac Atom Dictionary for Interpretable Neural Concept Extraction from ECG Foundation Models
Yixuan Duan, Arjun Naik, Sadeer Al-Kindi +1
Foundation models for 12-lead electrocardiograms (ECGs) transfer well across clinical tasks, but the physiological knowledge encoded in their representations remains opaque. We pre…