Document-Level Text Simplification: Dataset, Criteria and Baseline
Renliang Sun, Hanqi Jin, Xiaojun Wan
Abstract
Text simplification is a valuable technique. However, current research is limited to sentence simplification. In this paper, we define and investigate a new task of document-level text simplification, which aims to simplify a document consisting of multiple sentences. Based on Wikipedia dumps, we first construct a large-scale dataset named D-Wikipedia and perform analysis and human evaluation on it to show that the dataset is reliable. Then, we propose a new automatic evaluation metric called D-SARI that is more suitable for the document-level simplification task. Finally, we select several representative models as baseline models for this task and perform automatic evaluation and human evaluation. We analyze the results and point out the shortcomings of the baseline models.
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Cited by top-tier papers6
- SIMSUM: Document-level Text Simplification via Simultaneous SummarizationSofia Blinova, Xinyu Zhou, Martin Jaggi, Carsten Eickhoff et al.ACL 2023 · 11 citations
- Dancing Between Success and Failure: Edit-level Simplification Evaluation using SALSADavid Heineman, Yao Dou, Mounica Maddela, Wei XuEMNLP 2023 · 5 citations
- SWiPE: A Dataset for Document-Level Simplification of Wikipedia PagesPhilippe Laban, Jesse Vig, Wojciech Kryscinski, Shafiq Joty et al.ACL 2023 · 5 citations
- Elaborative Simplification as Implicit Questions Under DiscussionYating Wu, William Sheffield, Kyle Mahowald, Junyi Jessy LiEMNLP 2023 · 4 citations
- Document-Level Text Generation with Minimum Bayes Risk Decoding using Optimal TransportYuu JinnaiACL 2025
Builds on3
- Neural CRF Model for Sentence Alignment in Text SimplificationChao Jiang, Mounica Maddela, Wuwei Lan, Yang Zhong et al.ACL 2020 · 103 citations
- Discourse Level Factors for Sentence Deletion in Text SimplificationYang Zhong, Chao Jiang, Wei Xu, Junyi Jessy LiAAAI 2020 · 57 citations
- Jointly Learning to Align and Summarize for Neural Cross-Lingual SummarizationYue Cao, Hui Liu, Xiaojun WanACL 2020 · 52 citations
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