3.2k citations · 3.2k across the 14 of their papers we have counts for
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Verb-ICL: Rethinking In-Context Learning for Structured Prediction
Fan Bai, Hengshuo Miao, Sanjit S Batra +3
Structured prediction tasks pose unique challenges for in-context learning (ICL): their compositional outputs require modeling fine-grained, token-level patterns that sentence-leve…
MedFabric: Gold Evidence Hides the Difficulty of Word-Level Medical Fabrication Detection
Tung Sum Thomas Kwok, Qian Qian, Xiaofeng Lin +8
Large language models fabricate in medicine, producing fluent statements that are factually wrong, so reliable fabrication detection is a prerequisite for clinical deployment. Repo…
MedicalBench: Evaluating Large Language Models Toward Improved Medical Concept Extraction
Zhichao Yang, Gregory D. Lyng, Sanjit Singh Batra +1
Medical concept extraction from electronic health records underpins many downstream applications, yet remains challenging because medically meaningful concepts are frequently impli…
XAIQA: Explainer-Based Data Augmentation for Extractive Question Answering
Joel Stremmel, Ardavan Saeedi, Hamid Hassanzadeh +4
Extractive question answering (QA) systems can enable physicians and researchers to query medical records, a foundational capability for designing clinical studies and understandin…
Surpassing GPT-4 Medical Coding with a Two-Stage Approach
Zhichao Yang, Sanjit Singh Batra, Joel Stremmel +1
Recent advances in large language models (LLMs) show potential for clinical applications, such as clinical decision support and trial recommendations. However, the GPT-4 LLM predic…