1 citations · 1 across the 3 of their papers we have counts for
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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…
Substance over Style: Evaluating Proactive Conversational Coaching Agents
Vidya Srinivas, Xuhai Xu, Xin Liu +5
While NLP research has made strides in conversational tasks, many approaches focus on single-turn responses with well-defined objectives or evaluation criteria. In contrast, coachi…
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 (…
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…
Can AI Relate: Testing Large Language Model Response for Mental Health Support
Saadia Gabriel, Isha Puri, Xuhai Xu +2
Large language models (LLMs) are already being piloted for clinical use in hospital systems like NYU Langone, Dana-Farber and the NHS. A proposed deployment use case is psychothera…
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…