mlsanityData to 14 Oct 2026

Iterative Edit-Based Unsupervised Sentence Simplification

arXiv 2006.09639 ↗First posted 17 Jun 2020cs.CLcited by 33

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Abstract (arXiv)

We present a novel iterative, edit-based approach to unsupervised sentence simplification. Our model is guided by a scoring function involving fluency, simplicity, and meaning preservation. Then, we iteratively perform word and phrase-level edits on the complex sentence. Compared with previous approaches, our model does not require a parallel training set, but is more controllable and interpretable. Experiments on Newsela and WikiLarge datasets show that our approach is nearly as effective as state-of-the-art supervised approaches.

Key facts. Cited by 33 papers in the map (data through 14 Oct 2026). First posted on arXiv 17 Jun 2020.

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Citing papers per year: 2021: 6; 2022: 10; 2023: 12; 2024: 3; 2025: 2.

33 papers.

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  1. 2022GrIPS: Gradient-free, Edit-based Instruction Search for Prompting Large Language Modelscited by 127
  2. 2022LENS: A Learnable Evaluation Metric for Text Simplificationcited by 54
  3. 2023Generating Summaries with Controllable Readability Levelscited by 24
  4. 2022Improving Iterative Text Revision by Learning Where to Edit from Other Revision Taskscited by 20
  5. 2022Text Revision by On-the-Fly Representation Optimizationcited by 17
  6. 2023Prompt-Based Editing for Text Style Transfercited by 16
  7. 2021Generating Fluent Fact Checking Explanations with Unsupervised Post-Editingcited by 15
  8. 2023Sentence Simplification via Large Language Modelscited by 15
  9. 2023Dancing Between Success and Failure: Edit-level Simplification Evaluation using SALSAcited by 15
  10. 2021An Unsupervised Method for Building Sentence Simplification Corpora in Multiple Languagescited by 14
  11. 2022Learning Non-Autoregressive Models from Search for Unsupervised Sentence Summarizationcited by 12
  12. 2021Machine-in-the-Loop Rewriting for Creative Image Captioningcited by 11
21 more
  1. 2024ReadCtrl: Personalizing text generation with readability-controlled instruction learningcited by 10
  2. 2024What Goes Into a LM Acceptability Judgment? Rethinking the Impact of Frequency and Lengthcited by 10
  3. 2021Search and Learn: Improving Semantic Coverage for Data-to-Text Generationcited by 8
  4. 2022GRS: Combining Generation and Revision in Unsupervised Sentence Simplificationcited by 6
  5. 2021Simulated annealing for optimization of graphs and sequencescited by 5
  6. 2022Improving Zero-Shot Event Extraction via Sentence Simplificationcited by 5
  7. 2023Exploiting Summarization Data to Help Text Simplificationcited by 5
  8. 2022StyleFlow: Disentangle Latent Representations via Normalizing Flow for Unsupervised Text Style Transfercited by 4
  9. 2023A New Dataset and Empirical Study for Sentence Simplification in Chinesecited by 4
  10. 2021Simulated Annealing for Emotional Dialogue Systemscited by 3
  11. 2023Context-Aware Document Simplificationcited by 3
  12. 2025Aligning Sentence Simplification with ESL Learner's Proficiency for Language Acquisitioncited by 3
  13. 2022Unsupervised Sentence Simplification via Dependency Parsingcited by 2
  14. 2023Search and Learning for Unsupervised Text Generationcited by 1
  15. 2023BoschAI @ PLABA 2023: Leveraging Edit Operations in End-to-End Neural Sentence Simplificationcited by 1
  16. 2024Edit-Constrained Decoding for Sentence Simplificationcited by 1
  17. 2025Classic4Children: Adapting Chinese Literary Classics for Children with Large Language Modelcited by 1
  18. 2022An Empirical Study on Learning and Improving the Search Objective for Unsupervised Paraphrasingcited by 0
  19. 2023Sentence Simplification Using Paraphrase Corpus for Initializationcited by 0
  20. 2023MCTS: A Multi-Reference Chinese Text Simplification Datasetcited by 0
  21. 2023Can Knowledge Graphs Simplify Text?cited by 0