mlsanityData to 14 Oct 2026

SWiPE: A Dataset for Document-Level Simplification of Wikipedia Pages

arXiv 2305.19204 ↗First posted 30 May 2023cs.CLcited by 12

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Abstract (arXiv)

Text simplification research has mostly focused on sentence-level simplification, even though many desirable edits - such as adding relevant background information or reordering content - may require document-level context. Prior work has also predominantly framed simplification as a single-step, input-to-output task, only implicitly modeling the fine-grained, span-level edits that elucidate the simplification process. To address both gaps, we introduce the SWiPE dataset, which reconstructs the document-level editing process from English Wikipedia (EW) articles to paired Simple Wikipedia (SEW) articles. In contrast to prior work, SWiPE leverages the entire revision history when pairing pages in order to better identify simplification edits. We work with Wikipedia editors to annotate 5,000 EW-SEW document pairs, labeling more than 40,000 edits with proposed 19 categories. To scale our efforts, we propose several models to automatically label edits, achieving an F-1 score of up to 70.6, indicating that this is a tractable but challenging NLU task. Finally, we categorize the edits produced by several simplification models and find that SWiPE-trained models generate more complex edits while reducing unwanted edits.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 32 of its 62 references that are in the map. First posted on arXiv 30 May 2023.

Builds on

32 of 62 references.

References · 32

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  10. 2017Sentence Simplification with Deep Reinforcement Learningcited by 109
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  12. 2020Neural CRF Model for Sentence Alignment in Text Simplificationcited by 106
20 more
  1. 2020ASSET: A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformationscited by 101
  2. 2019Encode, Tag, Realize: High-Precision Text Editingcited by 99
  3. 2022PEER: A Collaborative Language Modelcited by 86
  4. 2018BLEU is Not Suitable for the Evaluation of Text Simplificationcited by 78
  5. 2019Controllable Sentence Simplificationcited by 78
  6. 2021Planning with Learned Entity Prompts for Abstractive Summarizationcited by 75
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  8. 2021Paragraph-level Simplification of Medical Textscited by 53
  9. 2021Keep it Simple: Unsupervised Simplification of Multi-Paragraph Textcited by 45
  10. 2022Evaluating Factuality in Text Simplificationcited by 34
  11. 2022EditEval: An Instruction-Based Benchmark for Text Improvementscited by 30
  12. 2020Elaborative Simplification: Content Addition and Explanation Generation in Text Simplificationcited by 27
  13. 2021Document-Level Text Simplification: Dataset, Criteria and Baselinecited by 27
  14. 2022arXivEdits: Understanding the Human Revision Process in Scientific Writingcited by 26
  15. 2022Text Generation with Text-Editing Modelscited by 21
  16. 2019Discourse Level Factors for Sentence Deletion in Text Simplificationcited by 19
  17. 2015Unsupervised Sentence Simplification Using Deep Semanticscited by 9
  18. 2022Mining Naturally-occurring Corrections and Paraphrases from Wikipedia's Revision Historycited by 4
  19. 2023Designing and Evaluating Interfaces that Highlight News Coverage Diversity Using Discord Questionscited by 3
  20. 2022Near-Negative Distinction: Giving a Second Life to Human Evaluation Datasetscited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 3; 2024: 5; 2025: 2; 2026: 2.

12 papers.

  1. 2024Aligning LLM Agents by Learning Latent Preference from User Editscited by 69
  2. 2024Can AI writing be salvaged? Mitigating Idiosyncrasies and Improving Human-AI Alignment in the Writing Process through Editscited by 49
  3. 2023Beyond the Chat: Executable and Verifiable Text-Editing with LLMscited by 35
  4. 2024InfoLossQA: Characterizing and Recovering Information Loss in Text Simplificationcited by 14
  5. 2024SciNews: From Scholarly Complexities to Public Narratives -- A Dataset for Scientific News Report Generationcited by 12
  6. 2024An Open Multilingual System for Scoring Readability of Wikipediacited by 7
  7. 2025Progressive Document-level Text Simplification via Large Language Modelscited by 5
  8. 2023Automatic and Human-AI Interactive Text Generationcited by 4
  9. 2023Medical Text Simplification: Optimizing for Readability with Unlikelihood Training and Reranked Beam Search Decodingcited by 3
  10. 2025Beyond In-Context Learning: Aligning Long-form Generation of Large Language Models via Task-Inherent Attribute Guidelinescited by 2
  11. 2026A Semiotics-Aware Framework for Evaluating Fidelity and Coverage in Natural Language Generationcited by 0
  12. 2026SPHERE: Adaptive VR Indoor Scene Generation via LLM-Enhanced Spatial Preference Learning and Human-in-the-Loop RLcited by 0