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Found 3 papers, 2 papers with code
Multi-Task Learning for Knowledge Graph Completion with Pre-trained Language Models
As research on utilizing human knowledge in natural language processing has attracted considerable attention in recent years, knowledge graph (KG) completion has come into the spotlight.
Zero-shot Triplet Extraction by Template Infilling
We propose a novel framework, ZETT (ZEro-shot Triplet extraction by Template infilling), that aligns the task objective to the pre-training objective of generative transformers to generalize to unseen relations.
Ranked #1 on
Zero-shot Relation Triplet Extraction
on FewRel
Data Augmentation for Rare Symptoms in Vaccine Side-Effect Detection
We study the problem of entity detection and normalization applied to patient self-reports of symptoms that arise as side-effects of vaccines.
