6 papers
AnchorSIPS: A Synthetic Dataset and Evaluation Resource for Evidence-Supported Psychosis-Risk Symptom Measurement
Guilherme C. Oliveira, Stephanie Fong, Zimu Wang +10
Progress on AI for psychosis-risk assessment is limited by a data-access bottleneck. Real clinical interviews are difficult to share because of privacy, governance, and consent con…
NeRD: Neuro-Symbolic Rule Distillation for Efficient Ontology-Grounded Chain-of-Thought in Medical Image Diagnosis
Hongxi Yang, Yiwen Jiang, Siyuan Yan +8
Interpretability is essential for trustworthy medical image diagnosis. However, existing concept-driven interpretable methods have key limitations: Concept Bottleneck Models (CBMs)…
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…
CHiRPE: A Step Towards Real-World Clinical NLP with Clinician-Oriented Model Explanations
Stephanie Fong, Zimu Wang, Guilherme C. Oliveira +9
The medical adoption of NLP tools requires interpretability by end users, yet traditional explainable AI (XAI) methods are misaligned with clinical reasoning and lack clinician inp…
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…