2 citations · 3 across the 7 of their papers we have counts for
7 papers
Do LLMs Need to See Everything? A Benchmark and Study of Failures in LLM-driven Smartphone Automation using Screentext vs. Screenshots
Shiquan Zhang, Tianyi Zhang, Le Fang +3
With the rapid advancement of large language models (LLMs), mobile agents have emerged as promising tools for phone automation, simulating human interactions on screens to accompli…
Menta: A Small Language Model for On-Device Mental Health Prediction
Tianyi Zhang, Xiangyuan Xue, Lingyan Ruan +6
Mental health conditions affect hundreds of millions globally, yet early detection remains limited. While large language models (LLMs) have shown promise in mental health applicati…
Behavioral Indicators of Loneliness: Predicting University Students' Loneliness Scores from Smartphone Sensing Data
Qianjie Wu, Tianyi Zhang, Hong Jia +1
Loneliness is a critical mental health issue among university students, yet traditional monitoring methods rely primarily on retrospective self-reports and often lack real-time beh…
AutoJournaling: A Context-Aware Journaling System Leveraging MLLMs on Smartphone Screenshots
Tianyi Zhang, Shiquan Zhang, Le Fang +3
Journaling offers significant benefits, including fostering self-reflection, enhancing writing skills, and aiding in mood monitoring. However, many people abandon the practice beca…
ScreenTK: Seamless Detection of Time-Killing Moments Using Continuous Mobile Screen Text and On-Device LLMs
Le Fang, Shiquan Zhang, Hong Jia +2
Smartphones have become essential to people's digital lives, providing a continuous stream of information and connectivity. However, this constant flow can lead to moments where us…
Enabling On-Device LLMs Personalization with Smartphone Sensing
Shiquan Zhang, Ying Ma, Le Fang +3
This demo presents a novel end-to-end framework that combines on-device large language models (LLMs) with smartphone sensing technologies to achieve context-aware and personalized…
Leveraging LLMs to Predict Affective States via Smartphone Sensor Features
Tianyi Zhang, Songyan Teng, Hong Jia +1
As mental health issues for young adults present a pressing public health concern, daily digital mood monitoring for early detection has become an important prospect. An active res…