5 citations · 6 across the 8 of their papers we have counts for
6 papers · 1 filter
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…
Explainable Graph Neural Networks: Understanding Brain Connectivity and Biomarkers in Dementia
Niharika Tewari, Nguyen Linh Dan Le, Mujie Liu +5
Dementia is a progressive neurodegenerative disorder with multiple etiologies, including Alzheimer's disease, Parkinson's disease, frontotemporal dementia, and vascular dementia. I…
LiteFat: Lightweight Spatio-Temporal Graph Learning for Real-Time Driver Fatigue Detection
Jing Ren, Suyu Ma, Hong Jia +5
Detecting driver fatigue is critical for road safety, as drowsy driving remains a leading cause of traffic accidents. Many existing solutions rely on computationally demanding deep…
Beyond Scale: Small Language Models are Comparable to GPT-4 in Mental Health Understanding
Hong Jia, Shiya Fu, Feng Xia +2
The emergence of Small Language Models (SLMs) as privacy-preserving alternatives for sensitive applications raises a fundamental question about their inherent understanding capabil…
Foundation Models for Anomaly Detection: Vision and Challenges
Jing Ren, Tao Tang, Hong Jia +6
As data continues to grow in volume and complexity across domains such as finance, manufacturing, and healthcare, effective anomaly detection is essential for identifying irregular…
ED-Filter: Dynamic Feature Filtering for Eating Disorder Classification
Mehdi Naseriparsa, Suku Sukunesan, Zhen Cai +4
Eating disorders (ED) are critical psychiatric problems that have alarmed the mental health community. Mental health professionals are increasingly recognizing the utility of data…