5 papers
Social Human Robot Embodied Conversation (SHREC) Dataset: Benchmarking Foundational Models' Social Reasoning
Dong Won Lee, Yubin Kim, Denison Guvenoz +5
Our work focuses on the social reasoning capabilities of foundation models for real-world human-robot interactions. We introduce the Social Human Robot Embodied Conversation (SHREC…
Aligning Dialogue Agents with Global Feedback via Large Language Model Multimodal Reward Decomposition
Dong Won Lee, Hae Won Park, Cynthia Breazeal +1
We propose a large language model based reward decomposition framework for aligning dialogue agents using only a single session-level feedback signal. We leverage the reasoning cap…
A Modern System Recipe for Situated Embodied Human-Robot Conversation with Real-Time Multimodal LLMs and Tool-Calling
Dong Won Lee, Sarah Gillet, Louis-Philippe Morency +2
Situated embodied conversation requires robots to interleave real-time dialogue with active perception: deciding what to look at, when to look, and what to say under tight latency…
Leveraging Large Language Models to Identify Conversation Threads in Collaborative Learning
Prerna Ravi, Dong Won Lee, Beatriz Flamia +5
Understanding how ideas develop and flow in small-group conversations is critical for analyzing collaborative learning. A key structural feature of these interactions is threading,…
Does "Reasoning" with Large Language Models Improve Recognizing, Generating, and Reframing Unhelpful Thoughts?
Yilin Qi, Dong Won Lee, Cynthia Breazeal +1
Cognitive Reframing, a core element of Cognitive Behavioral Therapy (CBT), helps individuals reinterpret negative experiences by finding positive meaning. Recent advances in Large…