3 papers
cs.CL2025
Retrieval-Augmented Generation for Electrocardiogram-Language Models
Xiaoyu Song, William Han, Tony Chen +4
Interest in generative Electrocardiogram-Language Models (ELMs) is growing, as they can produce textual responses conditioned on ECG signals and textual queries. Unlike traditional…
cs.AI2025
Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework
William Han, Chaojing Duan, Zhepeng Cen +7
Recent advances have increasingly applied large language models (LLMs) to electrocardiogram (ECG) interpretation, giving rise to Electrocardiogram-Language Models (ELMs). Condition…
cs.CL2024
ECG-Byte: A Tokenizer for End-to-End Generative Electrocardiogram Language Modeling
William Han, Chaojing Duan, Michael A. Rosenberg +2
Large Language Models (LLMs) have demonstrated exceptional versatility across domains, including applications to electrocardiograms (ECGs). A growing body of work focuses on genera…