7 papers
Dementia-Agents: A Multi-Modal Multi-Agent System for Dementia Staging and Phenotyping
Yaling Shen, Maja Christensen, Yiwen Jiang +4
Dementia diagnosis requires integrating multi-modal clinical assessments from diverse informants and clinicians under incomplete and heterogeneous data conditions. Yet most AI-driv…
AudioProcessBench: Benchmark for Identifying Process Errors in Audio-Grounded Reasoning
Xiangyu Zhao, Junyu Yan, Yaling Shen +7
Large audio-language models (LALMs) increasingly use explicit reasoning traces for complex audio understanding, yet the evaluation of reasoning quality remains underexplored. Altho…
Do No Harm: Exposing Hidden Vulnerabilities of LLMs via Persona-based Client Simulation Attack in Psychological Counseling
Qingyang Xu, Yaling Shen, Stephanie Fong +7
The increasing use of large language models (LLMs) in mental healthcare raises safety concerns in high-stakes therapeutic interactions. A key challenge is distinguishing therapeuti…
Tears or Cheers? Benchmarking LLMs via Culturally Elicited Distinct Affective Responses
Chongyuan Dai, Yaling Shen, Jinpeng Hu +6
Culture serves as a fundamental determinant of human affective processing and profoundly shapes how individuals perceive and interpret emotional stimuli. Despite this intrinsic lin…
PsychEthicsBench: Evaluating Large Language Models Against Australian Mental Health Ethics
Yaling Shen, Stephanie Fong, Yiwen Jiang +9
The increasing integration of large language models (LLMs) into mental health applications necessitates robust frameworks for evaluating professional safety alignment. Current eval…
It Hears, It Sees too: Multi-Modal LLM for Depression Detection By Integrating Visual Understanding into Audio Language Models
Xiangyu Zhao, Yaling Shen, Yiwen Jiang +7
Depression is one of the most prevalent mental health disorders globally. In recent years, multi-modal data, such as speech, video, and transcripts, has been increasingly used to d…