activity
20242026
most citedA Foundation Model for Wearable Movement Data in Mental Health Research

2 citations · 2 across the 4 of their papers we have counts for

collaborators
Showing 2026Show all

6 papers · 1 filter

cs.CL2026

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…

cs.AI2026

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…

cs.CL2026

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…

cs.AI2026

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…

cs.CL2026

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.…

cs.AI2026

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…