Papers with edit operation

4 papers
GRS: Combining Generation and Revision in Unsupervised Sentence Simplification (2022.findings-acl)

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Challenge: Existing methods for sentence simplification are supervised or unsupervised . paraphrasing captures complex edit operations, while revision-based methods provide more control and interpretability.
Approach: They propose an unsupervised approach to sentence simplification that combines text generation and text revision.
Outcome: The proposed method improves on the Newsela and ASSET datasets.
Automatic Decomposition of Text Editing Examples into Primitive Edit Operations: Toward Analytic Evaluation of Editing Systems (2024.lrec-main)

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Challenge: Existing methods to automate text editing tasks are blackboxed and do not understand the behavior of the systems.
Approach: They propose a task of automatic decomposition of text editing examples into primitive edit operations by using a phrase aligner and a large language model.
Outcome: The proposed method perfectly decomposes 44% and 64% of editing examples . Detailed analyses also provide insights into the difficulties of this task .
Seq2Edits: Sequence Transduction Using Span-level Edit Operations (2020.emnlp-main)

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Challenge: Seq2Edits is an open-vocabulary approach to sequence editing for natural language processing tasks with a high degree of overlap between input and output texts.
Approach: They propose an open-vocabulary approach to sequence editing for NLP tasks with a high degree of overlap between input and output texts.
Outcome: The proposed approach speeds up inference by up to 5.2x compared to full sequence models . it improves explainability by associating each edit operation with a human-readable tag.
Edit-Constrained Decoding for Sentence Simplification (2024.findings-emnlp)

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Challenge: Existing studies have shown that lexically constrained decoding is effective for sentence simplification, but their constraints can be loose and may lead to sub-optimal generation.
Approach: They propose an edit operation based on lexically constrained decoding for sentence simplification using a dictionary of technical terms as constraints.
Outcome: The proposed method outperforms previous studies on English simplification corpora and is based on lexical paraphrasing.

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