activity
20242026
most citedExpresso-AI: Explainable Video-Based Deep Learning Models for Depression Diagnosis

3 citations · 3 across the 1 of their papers we have counts for

collaborators

7 papers

cs.CV20263 cited

Expresso-AI: Explainable Video-Based Deep Learning Models for Depression Diagnosis

Felipe Moreno, Sharifa Alghowinem, Hae Won Park +1

Given the widespread prevalence of depression and its consequential impact on individuals and society, it is crucial to obtain objective measures for early diagnosis and interventi…

cs.CL2025

Ensembling Large Language Models to Characterize Affective Dynamics in Student-AI Tutor Dialogues

Chenyu Zhang, Sharifa Alghowinem, Cynthia Breazeal

While recent studies have examined the leaning impact of large language model (LLM) in educational contexts, the affective dynamics of LLM-mediated tutoring remain insufficiently u…

cs.HC2025

Social Robots as Social Proxies for Fostering Connection and Empathy Towards Humanity

Jocelyn Shen, Audrey Lee, Sharifa Alghowinem +3

Despite living in an increasingly connected world, social isolation is a prevalent issue today. While social robots have been explored as tools to enhance social connection through…

cs.CL2024

A Demonstration of Adaptive Collaboration of Large Language Models for Medical Decision-Making

Yubin Kim, Chanwoo Park, Hyewon Jeong +7

Medical Decision-Making (MDM) is a multi-faceted process that requires clinicians to assess complex multi-modal patient data patient, often collaboratively. Large Language Models (…

cs.CL2024

MDAgents: An Adaptive Collaboration of LLMs for Medical Decision-Making

Yubin Kim, Chanwoo Park, Hyewon Jeong +7

Foundation models are becoming valuable tools in medicine. Yet despite their promise, the best way to leverage Large Language Models (LLMs) in complex medical tasks remains an open…

cs.CL2024

Can Language Models Take A Hint? Prompting for Controllable Contextualized Commonsense Inference

Pedro Colon-Hernandez, Nanxi Liu, Chelsea Joe +5

Generating commonsense assertions within a given story context remains a difficult task for modern language models. Previous research has addressed this problem by aligning commons…