2 citations · 2 across the 4 of their papers we have counts for
8 papers
Scaling Therapy Supervision: Assessing Psychotherapy Fidelity Using Large Language Models
Arvind Pillai, Alexis Roach, Jason Holden +11
Psychotherapy fidelity assessment measures how faithfully a therapist adheres to a treatment protocol, a critical determinant of positive patient outcomes. However, fidelity assess…
MontageFlow: Physically Valid High Fidelity EEG Generation
Sudarshan Regmi, Nabaraj Subedi, Arvind Pillai +6
Generative modeling offers a promising solution to the scarcity of labeled clinical electroencephalography (EEG) data under strict privacy constraints. Although recent generative m…
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…
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…
A Foundation Model for Wearable Movement Data in Mental Health Research
Franklin Y. Ruan, Aiwei Zhang, Jenny Y. Oh +2
Wearable movement data is collected by nearly all commercially available smartwatches and is a valuable resource for mental health research, reflecting fine-grained temporal behavi…