mlsanityData to 7 Oct 2026

Edit-Constrained Decoding for Sentence Simplification

arXiv 2409.19247 ↗First posted 28 Sep 2024cs.CL cs.AIcited by 1

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Abstract (arXiv)

We propose edit operation based lexically constrained decoding for sentence simplification. In sentence simplification, lexical paraphrasing is one of the primary procedures for rewriting complex sentences into simpler correspondences. While previous studies have confirmed the efficacy of lexically constrained decoding on this task, their constraints can be loose and may lead to sub-optimal generation. We address this problem by designing constraints that replicate the edit operations conducted in simplification and defining stricter satisfaction conditions. Our experiments indicate that the proposed method consistently outperforms the previous studies on three English simplification corpora commonly used in this task.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 28 of its 56 references that are in the map. First posted on arXiv 28 Sep 2024.

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28 of 56 references.

References · 28

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  6. 2023Grammar-Constrained Decoding for Structured NLP Tasks without Finetuningcited by 186
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  11. 2016Guided Open Vocabulary Image Captioning with Constrained Beam Searchcited by 105
  12. 2020ASSET: A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformationscited by 101
16 more
  1. 2018CGMH: Constrained Sentence Generation by Metropolis-Hastings Samplingcited by 93
  2. 2019EditNTS: An Neural Programmer-Interpreter Model for Sentence Simplification through Explicit Editingcited by 63
  3. 2020Felix: Flexible Text Editing Through Tagging and Insertioncited by 58
  4. 2019EASSE: Easier Automatic Sentence Simplification Evaluationcited by 50
  5. 2023KCTS: Knowledge-Constrained Tree Search Decoding with Token-Level Hallucination Detectioncited by 43
  6. 2023BLESS: Benchmarking Large Language Models on Sentence Simplificationcited by 34
  7. 2020Iterative Edit-Based Unsupervised Sentence Simplificationcited by 33
  8. 2018Unsupervised Neural Text Simplificationcited by 29
  9. 2021Text Simplification by Taggingcited by 27
  10. 2019Complexity-Weighted Loss and Diverse Reranking for Sentence Simplificationcited by 20
  11. 2019Transforming Complex Sentences into a Semantic Hierarchycited by 15
  12. 2021Neural semi-Markov CRF for Monolingual Word Alignmentcited by 15
  13. 2023Language Models for German Text Simplification: Overcoming Parallel Data Scarcity through Style-specific Pre-trainingcited by 15
  14. 2023Dancing Between Success and Failure: Edit-level Simplification Evaluation using SALSAcited by 15
  15. 2020AutoMeTS: The Autocomplete for Medical Text Simplificationcited by 12
  16. 2022GRS: Combining Generation and Revision in Unsupervised Sentence Simplificationcited by 6

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