1 citations · 1 across the 6 of their papers we have counts for
5 papers · 1 filter
BehaviorSFT: Behavioral Token Conditioning for Clinical Agents Across the Proactivity Spectrum
Yubin Kim, Zhiyuan Hu, Hyewon Jeong +11
Large Language Models (LLMs) as clinical agents require careful behavioral adaptation. While adept at reactive tasks (e.g., diagnosis reasoning), LLMs often struggle with proactive…
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…
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…
Medical Hallucinations in Foundation Models and Their Impact on Healthcare
Yubin Kim, Hyewon Jeong, Shan Chen +24
Hallucinations in foundation models arise from autoregressive training objectives that prioritize token-likelihood optimization over epistemic accuracy, fostering overconfidence an…
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 (…