45 citations · 94 across the 6 of their papers we have counts for
6 papers
Assessing Risks of Large Language Models in Mental Health Support: A Framework for Automated Clinical AI Red Teaming
Ian Steenstra, Paola Pedrelli, Weiyan Shi +2
Large Language Models (LLMs) are increasingly utilized for mental health support; however, current safety benchmarks often fail to detect the complex, longitudinal risks inherent i…
A Risk Ontology for Evaluating AI-Powered Psychotherapy Virtual Agents
Ian Steenstra, Timothy W. Bickmore
The proliferation of Large Language Models (LLMs) and Intelligent Virtual Agents acting as psychotherapists presents significant opportunities for expanding mental healthcare acces…
Scaffolding Empathy: Training Counselors with Simulated Patients and Utterance-level Performance Visualizations
Ian Steenstra, Farnaz Nouraei, Timothy W. Bickmore
Learning therapeutic counseling involves significant role-play experience with mock patients, with current manual training methods providing only intermittent granular feedback. We…
Virtual Agents for Alcohol Use Counseling: Exploring LLM-Powered Motivational Interviewing
Ian Steenstra, Farnaz Nouraei, Mehdi Arjmand +1
We introduce a novel application of large language models (LLMs) in developing a virtual counselor capable of conducting motivational interviewing (MI) for alcohol use counseling.…
Empathic Grounding: Explorations using Multimodal Interaction and Large Language Models with Conversational Agents
Mehdi Arjmand, Farnaz Nouraei, Ian Steenstra +1
We introduce the concept of "empathic grounding" in conversational agents as an extension of Clark's conceptualization of grounding in conversation in which the grounding criterion…
Multimodal Dialogue State Tracking By QA Approach with Data Augmentation
Xiangyang Mou, Brandyn Sigouin, Ian Steenstra +1
Recently, a more challenging state tracking task, Audio-Video Scene-Aware Dialogue (AVSD), is catching an increasing amount of attention among researchers. Different from purely te…