9 citations · 14 across the 4 of their papers we have counts for
4 papers · 1 filter
MEDEC: A Benchmark for Medical Error Detection and Correction in Clinical Notes
Asma Ben Abacha, Wen-wai Yim, Yujuan Fu +4
Several studies showed that Large Language Models (LLMs) can answer medical questions correctly, even outperforming the average human score in some medical exams. However, to our k…
Does Data Contamination Detection Work (Well) for LLMs? A Survey and Evaluation on Detection Assumptions
Yujuan Fu, Ozlem Uzuner, Meliha Yetisgen +1
Large language models (LLMs) have demonstrated great performance across various benchmarks, showing potential as general-purpose task solvers. However, as LLMs are typically traine…
BioMistral-NLU: Towards More Generalizable Medical Language Understanding through Instruction Tuning
Yujuan Velvin Fu, Giridhar Kaushik Ramachandran, Namu Park +4
Large language models (LLMs) such as ChatGPT are fine-tuned on large and diverse instruction-following corpora, and can generalize to new tasks. However, those instruction-tuned LL…
CACER: Clinical Concept Annotations for Cancer Events and Relations
Yujuan Fu, Giridhar Kaushik Ramachandran, Ahmad Halwani +5
Clinical notes contain unstructured representations of patient histories, including the relationships between medical problems and prescription drugs. To investigate the relationsh…