New preprint on clinical event extractionAug 1, 2022 PreprintIn DICE, we introduce a data-efficient generative model for clinical event extraction and propose the first benchmark in the domain. DICE: Data-Efficient Clinical Event Extraction with Generative ModelsMingyu Derek Ma, Alexander K. Taylor, Wei Wang, Nanyun PengACL, 2023We introduce DICE, a robust and data-efficient generative model for clinical event extraction, which specializes in clinical mention identification, and MACCROBAT-EE, the first clinical event extraction dataset with event argument annotation. PDF Cite Code Dataset Poster Slides Video DOI ACL AnthologyPreprint