activity
20242026
collaborators

13 papers

cs.LG2026

TimeRLM: Recursive Language Models Enable Precise Anomaly Localization in Long-Context Time-Series

Nicolas Zumarraga, Lorenzo Steno, Ning Wang +9

Precise anomaly localization over long-context time series is a crucial task in monitoring applications across clinical care, industrial operations, financial services, and logisti…

cs.HC2026

The ABC of digital health: A framework for translating digital health interventions into real-world applications

David Grüning, Vincent Beermann, Jan Enkmann +3

Research-based digital health interventions are often presented as potential solutions for extending health care in the real world. Yet the vast majority of these interventions fai…

cs.LG2026

TS-Haystack: A Multi-Task Retrieval Benchmark for Long-Context Time-Series Reasoning

Nicolas Zumarraga, Thomas Kaar, Ning Wang +12

Time Series Language Models (TSLMs) promise reasoning over real-world temporal data, but their ability to retrieve and reason over long time-series remains largely untested. We int…

cs.LG2026

OpenMHC: Accelerating the Science of Wearable Foundation Models

Narayan Schuetz, Yuze Bai, Lianggang Pan +16

Mobile and wearable devices offer an unprecedented opportunity for continuous, passive health monitoring and active health coaching. However, the largest wearable datasets are not…

cs.SD2026

Patient-Level Multimodal Question Answering from Multi-Site Auscultation Recordings

Fan Wu, Tsai-Ning Wang, Nicolas Zumarraga +8

Auscultation is a vital diagnostic tool, yet its utility is often limited by subjective interpretation. While general-purpose Audio-Language Models (ALMs) excel in general domains,…

cs.AI2026

How Well Do Multimodal Models Reason on ECG Signals?

Maxwell A. Xu, Harish Haresamudram, Catherine W. Liu +11

While multimodal large language models offer a promising solution to the "black box" nature of health AI by generating interpretable reasoning traces, verifying the validity of the…