4 papers
LENS: LLM-Enabled Narrative Synthesis for Mental Health by Aligning Multimodal Sensing with Language Models
Wenxuan Xu, Arvind Pillai, Subigya Nepal +6
Multimodal health sensing offers rich behavioral signals for assessing mental health, yet translating these numerical time-series measurements into natural language remains challen…
Learning Transferable Sensor Models via Language-Informed Pretraining
Yuliang Chen, Arvind Pillai, Yu Yvonne Wu +5
Modern sensing systems generate large volumes of unlabeled multivariate time-series data. This abundance of unlabeled data makes self-supervised learning (SSL) a natural approach f…
MotionTeller: Multi-modal Integration of Wearable Time-Series with LLMs for Health and Behavioral Understanding
Aiwei Zhang, Arvind Pillai, Andrew Campbell +1
As wearable sensing becomes increasingly pervasive, a key challenge remains: how can we generate natural language summaries from raw physiological signals such as actigraphy - minu…
Time2Lang: Bridging Time-Series Foundation Models and Large Language Models for Health Sensing Beyond Prompting
Arvind Pillai, Dimitris Spathis, Subigya Nepal +6
Large language models (LLMs) show promise for health applications when combined with behavioral sensing data. Traditional approaches convert sensor data into text prompts, but this…