Awesome

Sequence Generation with Label Augmentation for Relation Extraction.
Bo Li, Dingyao Yu, Wei Ye, Jinglei Zhang, Shikun Zhang. AAAI2023 Oral Paper

This paper investigates the merits of employing sequence generation in relation extraction, finding that with relation names or synonyms as generation targets, their textual semantics and the correlation (in terms of word sequence pattern) among them affect model performance.

We hope our work could encourage the community to make further exploration and breakthrough towards better Seq2Seq-based RE models.