SUBS: Subtree Substitution for Compositional Semantic Parsing

Anonymous

Paper Link: https://openreview.net/forum?id=6iScGvJZfat

Paper Type: Short paper (up to four pages of content + unlimited references and appendices)

Abstract: Although sequence-to-sequence models often achieve good performance in semantic parsing for i.i.d. data, their performance is still inferior in compositional generalization. Several data augmentation methods have been proposed to alleviate this problem. However, prior work only leveraged superficial grammar or rules for data augmentation, which resulted in limited improvement. We propose to use subtree substitution for compositional data augmentation, where we consider subtrees with similar semantic functions as exchangeable. Our experiments showed that such augmented data led to significantly better performance on Scan and GeoQuery, and reached new SOTA on compositional split of GeoQuery.

Presentation Mode: This paper will be presented in person in Seattle

Copyright Consent Signature (type Name Or NA If Not Transferrable): NA

Copyright Consent Name And Address: Georgia Institute of Technology