Papers with text simplification tasks

2 papers
Teaching the Pre-trained Model to Generate Simple Texts for Text Simplification (2023.findings-acl)

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Challenge: Existing strategies to teach pre-trained models to generate simple texts are inadequate.
Approach: They propose a continued pre-training strategy to teach pre-trained models to generate simple texts by randomly masking text spans in ordinary texts.
Outcome: The proposed strategy improves on lexical simplification, sentence simplification and document-level simplification tasks over existing models.
Label Confidence Weighted Learning for Target-level Sentence Simplification (2024.emnlp-main)

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Challenge: Existing methods for sentence simplification use label confidence weighting to generate pseudo-labeled sentences with varying proficiency levels.
Approach: They propose a label confidence weighting scheme for multi-level sentence simplification that incorporates a weighting system into the training loss of the encoder-decoder model.
Outcome: The proposed approach outperforms state-of-the-art confidence weighting methods on English grade-level simplification datasets.

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