1 citations · 1 across the 6 of their papers we have counts for
9 papers
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…
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…
Towards Objective Obstetric Ultrasound Assessment: Contrastive Representation Learning for Fetal Movement Detection
Talha Ilyas, Duong Nhu, Allison Thomas +13
Accurate fetal movement (FM) detection is essential for assessing prenatal health, as abnormal movement patterns can indicate underlying complications such as placental dysfunction…
WISE: Weak-Supervision-Guided Step-by-Step Explanations for Multimodal LLMs in Image Classification
Yiwen Jiang, Deval Mehta, Siyuan Yan +3
Multimodal Large Language Models (MLLMs) have shown promise in visual-textual reasoning, with Multimodal Chain-of-Thought (MCoT) prompting significantly enhancing interpretability.…
Enhancing Interpretable Image Classification Through LLM Agents and Conditional Concept Bottleneck Models
Yiwen Jiang, Deval Mehta, Wei Feng +1
Concept Bottleneck Models (CBMs) decompose image classification into a process governed by interpretable, human-readable concepts. Recent advances in CBMs have used Large Language…