1 citations · 1 across the 14 of their papers we have counts for
16 papers
Steering the Compass: Aligning Dynamic Psychological Counseling Conversations with Cognitive Behavioral Therapy Strategies
Zimu Wang, Yiwen Jiang, Xiangyu Zhao +10
Recent advancements in large language models have revolutionized the field of psychological counseling, especially in the context of Cognitive Behavioral Therapy (CBT). While the s…
SDARE-Bench: Evaluating Large Language Models on Conversational Stigma Detection and Response in Dyadic and Group Dialogue
Stephanie Fong, Yiwen Jiang, Zimu Wang +12
Large Language Models (LLMs) are increasingly used in advice seeking and decision making that may affect social judgements. Despite stigma's profound effects on people and communit…
VIBE-Bench: Evaluating Personalized Large Language Models When Profiles Don't Mean Preferences
Yiwen Jiang, Yang Deng, Stephanie Fong +9
Personalized Large Language Models (PLLMs) aim to tailor responses to individual users, where a central challenge is preference reasoning: inferring query-relevant preferences from…
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…
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…
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…
Neurosymbolic Framework for Concept-Driven Logical Reasoning in Skeleton-Based Human Action Recognition
Talha Ilyas, Deval Mehta, Zongyuan Ge
Skeleton-based human activity recognition has achieved strong empirical performance, yet most existing models remain black boxes and difficult to interpret. In this work, we introd…
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…
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…
Interpretable Few-Shot Retinal Disease Diagnosis with Concept-Guided Prompting of Vision-Language Models
Deval Mehta, Yiwen Jiang, Catherine L Jan +3
Recent advancements in deep learning have shown significant potential for classifying retinal diseases using color fundus images. However, existing works predominantly rely exclusi…
Adaptive Transformer Modelling of Density Function for Nonparametric Survival Analysis
Xin Zhang, Deval Mehta, Yanan Hu +8
Survival analysis holds a crucial role across diverse disciplines, such as economics, engineering and healthcare. It empowers researchers to analyze both time-invariant and time-va…