An intuitive way for a human to write paraphrase sentences is to replace
words or phrases in the original sentence with their corresponding synonyms and
make necessary changes to ensure the new sentences are fluent and grammatically
correct. We propose a novel approach to modeling the process with
dictionary-guided editing networks which effectively conduct rewriting on the
source sentence to generate paraphrase sentences. It jointly learns the
selection of the appropriate word level and phrase level paraphrase pairs in
the context of the original sentence from an off-the-shelf dictionary as well
as the generation of fluent natural language sentences. Specifically, the
system retrieves a set of word level and phrase level araphrased pairs derived
from the Paraphrase Database (PPDB) for the original sentence, which is used to
guide the decision of which the words might be deleted or inserted with the
soft attention mechanism under the sequence-to-sequence framework. We conduct
experiments on two benchmark datasets for paraphrase generation, namely the
MSCOCO and Quora dataset. The evaluation results demonstrate that our
dictionary-guided editing networks outperforms the baseline methods.

本文提出了利用字典引导的编辑网络模型来生成同义句的方法，并在两个基准数据集上进行了实验，证明其比基线方法表现更好。