Xiaolian Zhang

ODDA: An OODA-Driven Diverse Data Augmentation Framework for Low-Resource Relation Extraction

Data Augmentation (DA) has emerged as a promising solution to address the scarcity of high-quality annotated data in low-resource relation extraction (LRE). Leveraging large language models (LLMs), DA has significantly improved the performance of RE models with considerably fewer parameters. However…