30 citations · 64 across the 12 of their papers we have counts for
13 papers
Drawing the Line: Where AI Guidance and Human Creativity Meet in Emotion-Driven Comic Storyboarding
Jocelyn Shen, Isabella Pu, Alessandro Briseño +5
While generative AI models can produce visually faithful artwork, they often fall short in conveying emotional authenticity--a key driver of human expression. In visual storytellin…
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…
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…
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…
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 (…
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…
A HeARTfelt Robot: Social Robot-Driven Deep Emotional Art Reflection with Children
Isabella Pu, Golda Nguyen, Lama Alsultan +3
Social-emotional learning (SEL) skills are essential for children to develop to provide a foundation for future relational and academic success. Using art as a medium for creation…
EmpathicStories++: A Multimodal Dataset for Empathy towards Personal Experiences
Jocelyn Shen, Yubin Kim, Mohit Hulse +4
Modeling empathy is a complex endeavor that is rooted in interpersonal and experiential dimensions of human interaction, and remains an open problem within AI. Existing empathy dat…
HEART-felt Narratives: Tracing Empathy and Narrative Style in Personal Stories with LLMs
Jocelyn Shen, Joel Mire, Hae Won Park +2
Empathy serves as a cornerstone in enabling prosocial behaviors, and can be evoked through sharing of personal experiences in stories. While empathy is influenced by narrative cont…
Improving Dialogue Agents by Decomposing One Global Explicit Annotation with Local Implicit Multimodal Feedback
Dong Won Lee, Hae Won Park, Yoon Kim +2
We describe an approach for aligning an LLM-based dialogue agent based on global (i.e., dialogue-level) rewards, while also taking into account naturally-occurring multimodal signa…
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…
Integrating Flow Theory and Adaptive Robot Roles: A Conceptual Model of Dynamic Robot Role Adaptation for the Enhanced Flow Experience in Long-term Multi-person Human-Robot Interactions
Huili Chen, Sharifa Alghowinem, Cynthia Breazeal +1
In this paper, we introduce a novel conceptual model for a robot's behavioral adaptation in its long-term interaction with humans, integrating dynamic robot role adaptation with pr…
Health-LLM: Large Language Models for Health Prediction via Wearable Sensor Data
Yubin Kim, Xuhai Xu, Daniel McDuff +2
Large language models (LLMs) are capable of many natural language tasks, yet they are far from perfect. In health applications, grounding and interpreting domain-specific and non-l…