DICE: Data-Efficient Clinical Event Extraction with Generative Models
We 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.
May 2, 2023
Implicit Discourse Relation Identification for Open-domain Dialogues
A novel dataset of implicit discourse relation argument pairs and labels for dialogic turns and a novel discourse relation identification pipeline specifically tuned for open-domain dialogue systems
Jul 28, 2019