21 citations · 21 across the 5 of their papers we have counts for
7 papers
Lapras: Latent Reasoning for Time Series Language Models
Yuliang Chen, Yu Yvonne Wu, Patrick Langer +11
Time Series Language Models (TSLMs) offer a promising path toward time series understanding by reasoning over temporal signals and producing natural language answers and explanatio…
TimeThink: Eliciting Compositional Reasoning in Timeseries Large Language Models
Sudarshan Regmi, Arvind Pillai, Yu Yvonne Wu +7
Timeseries multimodal large language models (TS-MLLMs) have recently begun leveraging the reasoning capabilities of large language models (LLMs) for question-answering tasks. Howev…
BALMS: Benchmarking Agentic LLMs for Longitudinal Mental Health Sensing
Yu Yvonne Wu, Arvind Pillai, Yuliang Chen +7
Mental health assessment relies on episodic self-report scales, which convert subjective states such as stress into numerical scores but provide only sparse snapshots of wellbeing.…
Learning Transferable Sensor Models via Language-Informed Pretraining
Yuliang Chen, Arvind Pillai, Yu Yvonne Wu +6
Multimodal language models have demonstrated strong semantic understanding and reasoning over physiological and behavioral signals captured from diverse healthcare sensors. However…
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…
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…
MoodCapture: Depression Detection Using In-the-Wild Smartphone Images
Subigya Nepal, Arvind Pillai, Weichen Wang +9
MoodCapture presents a novel approach that assesses depression based on images automatically captured from the front-facing camera of smartphones as people go about their daily liv…