13 citations · 16 across the 5 of their papers we have counts for
7 papers
Conditional Accuracy Profiles: Diagnosing LLM Judges across Deployment Conditions
Wenqi Li, Bin Liu, Mindi Ruan +3
LLM-as-judge is now a standard tool for scalable evaluation, but judge performance is still often summarized by a single accuracy number. This aggregate view hides the deployment c…
A Deterministic Evidence Layer for Vision-Language Autism Screening from Naturalistic Home Video
Wenqi Li, Mindi Ruan, Chuanbo Hu +2
Autism spectrum disorder (ASD) is diagnosed through specialist observation of a child's social behavior, and access to that expertise is the bottleneck for early identification. Vi…
Video-based Analysis Reveals Atypical Social Gaze in People with Autism Spectrum Disorder
Xiangxu Yu, Mindi Ruan, Chuanbo Hu +4
In this study, we present a quantitative and comprehensive analysis of social gaze in people with autism spectrum disorder (ASD). Diverging from traditional first-person camera per…
Exploring Speech Pattern Disorders in Autism using Machine Learning
Chuanbo Hu, Jacob Thrasher, Wenqi Li +5
Diagnosing autism spectrum disorder (ASD) by identifying abnormal speech patterns from examiner-patient dialogues presents significant challenges due to the subtle and diverse mani…
Exploiting ChatGPT for Diagnosing Autism-Associated Language Disorders and Identifying Distinct Features
Chuanbo Hu, Wenqi Li, Mindi Ruan +5
Diagnosing language disorders associated with autism is a complex challenge, often hampered by the subjective nature and variability of traditional assessment methods. Traditional…
UPDExplainer: an Interpretable Transformer-based Framework for Urban Physical Disorder Detection Using Street View Imagery
Chuanbo Hu, Shan Jia, Fan Zhang +4
Urban Physical Disorder (UPD), such as old or abandoned buildings, broken sidewalks, litter, and graffiti, has a negative impact on residents' quality of life. They can also increa…
Video-based Contrastive Learning on Decision Trees: from Action Recognition to Autism Diagnosis
Mindi Ruan, Xiangxu Yu, Na Zhang +3
How can we teach a computer to recognize 10,000 different actions? Deep learning has evolved from supervised and unsupervised to self-supervised approaches. In this paper, we prese…