6 papers
K9-Bench: Evaluating Multimodal LLMs on Canine-Centric Videos
Khush Attarde, Yusuf Ali, Megha Thukral +3
MLLMs have shown strong zero-shot capabilities across diverse inputs such as across images, video, audio, and text. A crucial, yet underexplored, application of these models lies i…
Hierarchical Modeling of ICD Codes in EHR Foundation Models
Megha Thukral, Dong Gyun Kang, Rudra Pratap Singh +3
Electronic health record foundation models typically treat ICD diagnosis codes as flat tokens, overlooking the clinically meaningful hierarchical structure that captures disease fa…
Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning
Hao Zhou, Simon A. Lee, Cyrus Tanade +12
Biosignals acquired from different locations on the body often provide temporally ordered views of the same underlying physiological process. However, most existing self supervised…
Wavelet-Driven Masked Multiscale Reconstruction for PPG Foundation Models
Megha Thukral, Cyrus Tanade, Simon A. Lee +10
Wearable foundation models have the potential to transform digital health by learning transferable representations from large-scale biosignals collected in everyday settings. While…
AgentSense: Virtual Sensor Data Generation Using LLM Agents in Simulated Home Environments
Zikang Leng, Megha Thukral, Yaqi Liu +4
A major challenge in developing robust and generalizable Human Activity Recognition (HAR) systems for smart homes is the lack of large and diverse labeled datasets. Variations in h…
HiMAE: Hierarchical Masked Autoencoders Discover Resolution-Specific Structure in Wearable Time Series
Simon A. Lee, Cyrus Tanade, Hao Zhou +13
Wearable sensors provide abundant physiological time series, yet the principles governing their predictive utility remain unclear. We hypothesize that temporal resolution is a fund…