论文标题
语法引导的受控释义
Syntax-guided Controlled Generation of Paraphrases
论文作者
论文摘要
给定一个句子（例如，“我喜欢芒果”）和一个约束（例如，情感翻转），受控文本生成的目标是产生一个适应输入句子以满足约束要求的句子（例如，“我讨厌芒果”）。超越了如此简单的限制，最近的工作已经开始探索复杂的句法指导作为受控释义的任务中的约束。在这些方法中，句法施用措施来自单独的示例性句子。但是，这些先前的作品仅利用了示例句子的解析树中可用的有限的句法信息。我们在论文中解决了此限制，并提出了语法引导的受控释义器（SGCP），这是句法释义生成的端到端框架。我们发现，SGCP可以生成语法符合句子，而不妥协相关性。我们对多个现实的英语数据集进行了广泛的自动化和人类评估，以证明SGCP对最先进的基线的功效。为了推动未来的研究，我们已经提供了SGCP的源代码
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 works have 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
