Edit-Constrained Decoding for Sentence Simplification
Tatsuya Zetsu, Yuki Arase, Tomoyuki Kajiwara
Abstract
We propose edit operation based lexically constrained decoding for sentence simplification. In sentence simplification, lexical paraphrasing is one of the primary procedures for rewriting complex sentences into simpler correspondences. While previous studies have confirmed the efficacy of lexically constrained decoding on this task, their constraints can be loose and may lead to sub-optimal generation. We address this problem by designing constraints that replicate the edit operations conducted in simplification and defining stricter satisfaction conditions. Our experiments indicate that the proposed method consistently outperforms the previous studies on three English simplification corpora commonly used in this task.
BibTeX
@inproceedings{zetsu-etal-2024-edit,
title = "Edit-Constrained Decoding for Sentence Simplification",
author = "Zetsu, Tatsuya and
Arase, Yuki and
Kajiwara, Tomoyuki",
editor = "Al-Onaizan, Yaser and
Bansal, Mohit and
Chen, Yun-Nung",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2024",
month = nov,
year = "2024",
address = "Miami, Florida, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.findings-emnlp.419/",
doi = "10.18653/v1/2024.findings-emnlp.419",
pages = "7161--7173"
}