Edit-Constrained Decoding for Sentence Simplification
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.
Code (1)
Tasks
SentenceSimilar Papers 제목 키워드 기반
EditNTS: An Neural Programmer-Interpreter Model for Sentence Simplification through Explicit Editing
We present the first sentence simplification model that learns explicit edit operations (ADD, DELETE, and KEEP) via a neural programmer-interpreter approach. Most current neural sentence simplification systems are varian…
Machine TranslationSentenceText SimplificationTranslationNegative Lexically Constrained Decoding for Paraphrase Generation
Paraphrase generation can be regarded as monolingual translation. Unlike bilingual machine translation, paraphrase generation rewrites only a limited portion of an input sentence. Hence, previous methods based on machine…
Machine TranslationParaphrase GenerationSentenceText Simplification+1A Constrained Sequence-to-Sequence Neural Model for Sentence Simplification
Sentence simplification reduces semantic complexity to benefit people with language impairments. Previous simplification studies on the sentence level and word level have achieved promising results but also meet great ch…
SentenceIterative Edit-Based Unsupervised Sentence Simplification
We present a novel iterative, edit-based approach to unsupervised sentence simplification. Our model is guided by a scoring function involving fluency, simplicity, and meaning preservation. Then, we iteratively perform w…
SentenceText SimplificationGRS: Combining Generation and Revision in Unsupervised Sentence Simplification
We propose GRS: an unsupervised approach to sentence simplification that combines text generation and text revision. We start with an iterative framework in which an input sentence is revised using explicit edit operatio…
SentenceText Generation