mlsanityData to 7 Oct 2026

Simplicity Level Estimate (SLE): A Learned Reference-Less Metric for Sentence Simplification

arXiv 2310.08170 ↗First posted 12 Oct 2023cs.CLcited by 14

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Abstract (arXiv)

Automatic evaluation for sentence simplification remains a challenging problem. Most popular evaluation metrics require multiple high-quality references -- something not readily available for simplification -- which makes it difficult to test performance on unseen domains. Furthermore, most existing metrics conflate simplicity with correlated attributes such as fluency or meaning preservation. We propose a new learned evaluation metric (SLE) which focuses on simplicity, outperforming almost all existing metrics in terms of correlation with human judgements.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Builds on 12 of its 28 references that are in the map. First posted on arXiv 12 Oct 2023.

Builds on

12 of 28 references.

References · 12

  1. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,462
  2. 2021QuestEval: Summarization Asks for Fact-based Evaluationcited by 241
  3. 2019Controllable Sentence Simplificationcited by 78
  4. 2022LENS: A Learnable Evaluation Metric for Text Simplificationcited by 54
  5. 2018Semantic Structural Evaluation for Text Simplificationcited by 30
  6. 2021Document-Level Text Simplification: Dataset, Criteria and Baselinecited by 27
  7. 2022On the Ethical Considerations of Text Simplificationcited by 20
  8. 2021Rethinking Automatic Evaluation in Sentence Simplificationcited by 17
  9. 2022A Neural Pairwise Ranking Model for Readability Assessmentcited by 14
  10. 2019Reference-less Quality Estimation of Text Simplification Systemscited by 10
  11. 2017A Sentence Simplification System for Improving Relation Extractioncited by 7
  12. 2023Context-Aware Document Simplificationcited by 3

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Citing papers per year: 2024: 7; 2025: 4; 2026: 3.

14 papers.

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