Exploiting Summarization Data to Help Text Simplification (2023)

Abstract: One of the major problems with text simplification is the lack of high-quality data. The sources of simplification datasets are limited to Wikipedia and Newsela, restricting further development of this field. In this paper, we analyzed the similarity between text summarization and text simplification and exploited summarization data to help simplify. First, we proposed an alignment algorithm to extract sentence pairs from summarization datasets. Then, we designed four attributes to characterize the degree of simplification and proposed a method to filter suitable pairs. We named these pairs Sum4Simp (S4S). Next, we conducted human evaluations to show that S4S is high-quality and compared it with a real simplification dataset. Finally, we conducted experiments to illustrate that the S4S can improve the performance of several mainstream simplification models, especially in low-resource scenarios.

## mine sentence pairs for simplification from summarization datasets in this section, we will elaborate on how to extract sentence pairs that are suitable for text simplification from text summarization datasets. text summarization is a document-level task while text simplification refers to a sentence-level task. thus, we proposed an algorithm to extract aligned sentence pairs at first. then, since not all aligned sentence pairs are suitable for text simplification, we chose four attributes and defined a set of rules to filter the appropriate sentence pairs. the whole process is shown in figure 1 . ## quantitative analysis in this section, we want to show that sum4simp (s4s) is high-quality. we conducted two human evaluations and performed statistics on s4s, comparing it with real simplification datasets. ## conclusion in this paper, we are committed to mining data from text summarization datasets to help text simplification. we proposed an alignment algorithm and a new method to filter suitable sentence pairs. we named these pairs sum4simp (s4s). we conducted human evaluations on s4s and performed experiments on mainstream simplification models to illustrate that the s4s is high-quality and can help text simplification. in future work, we will apply our method to mine more simplification data from other summarization datasets.