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Syntax-Guided Controlled Generation of Paraphrases

Authors :
Kumar, Ashutosh
Ahuja, Kabir
Vadapalli, Raghuram
Talukdar, Partha
Source :
Transactions of the Association for Computational Linguistics, Vol 8, Pp 330-345 (2020)
Publication Year :
2020
Publisher :
The MIT Press, 2020.

Abstract

Given a sentence (e.g., “I like mangoes”) and a constraint (e.g., sentiment flip), the goal of controlled text generation is to produce a sentence that adapts the input sentence to meet the requirements of the constraint (e.g., “I hate mangoes”). Going beyond such simple constraints, recent work has started exploring the incorporation of complex syntactic-guidance as constraints in the task of controlled paraphrase generation. In these methods, syntactic-guidance is sourced from a separate exemplar sentence. However, these prior works have only utilized limited syntactic information available in the parse tree of the exemplar sentence. We address this limitation in the paper and propose Syntax Guided Controlled Paraphraser (SGCP), an end-to-end framework for syntactic paraphrase generation. We find that Sgcp can generate syntax-conforming sentences while not compromising on relevance. We perform extensive automated and human evaluations over multiple real-world English language datasets to demonstrate the efficacy of Sgcp over state-of-the-art baselines. To drive future research, we have made Sgcp’s source code available. 1

Details

Language :
English
ISSN :
2307387X
Volume :
8
Database :
Directory of Open Access Journals
Journal :
Transactions of the Association for Computational Linguistics
Publication Type :
Academic Journal
Accession number :
edsdoj.365840afae7463fbedfb5706e93ee49
Document Type :
article
Full Text :
https://doi.org/10.1162/tacl_a_00318