activity
20242026
collaborators

8 papers

cs.HC2026

User Perceptions of an LLM-Based Chatbot for Cognitive Reappraisal of Stress: Feasibility Study

Ananya Bhattacharjee, Jina Suh, Mohit Chandra +1

Cognitive reappraisal is a well-studied emotion regulation strategy that helps individuals reinterpret stressful situations to reduce their impact. Many digital mental health tools…

cs.CL2026

AI generates well-liked but templatic empathic responses

Emma S. Gueorguieva, Hongli Zhan, Jina Suh +4

Recent research shows that greater numbers of people are turning to Large Language Models (LLMs) for emotional support, and that people rate LLM responses as more empathic than hum…

cs.CL2026

Discourse Diversity in Multi-Turn Empathic Dialogue

Hongli Zhan, Emma S. Gueorguieva, Javier Hernandez +3

Large language models (LLMs) produce responses rated as highly empathic in single-turn settings (Ayers et al., 2023; Lee et al., 2024), yet they are also known to be formulaic gene…

cs.HC2026

RESPOND: Responsive Engagement Strategy for Predictive Orchestration and Dialogue

Meng-Chen Lee, Costas Panay, Javier Hernandez +4

The majority of voice-based conversational agents still rely on pause-and-respond turn-taking, leaving interactions sounding stiff and robotic. We present RESPOND (Responsive Engag…

cs.HC2025

From Measurement to Expertise: Empathetic Expert Adapters for Context-Based Empathy in Conversational AI Agents

Erfan Shayegani, Jina Suh, Andy Wilson +2

Empathy is a critical factor in fostering positive user experiences in conversational AI. While models can display empathy, it is often generic rather than tailored to specific tas…

cs.HC2025

From Lived Experience to Insight: Unpacking the Psychological Risks of Using AI Conversational Agents

Mohit Chandra, Suchismita Naik, Denae Ford +8

Recent gains in popularity of AI conversational agents have led to their increased use for improving productivity and supporting well-being. While previous research has aimed to un…