@inproceedings{cripwell-etal-2023-document,
title = "Document-Level Planning for Text Simplification",
author = {Cripwell, Liam and
Legrand, Jo{\"e}l and
Gardent, Claire},
booktitle = "Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics",
month = may,
year = "2023",
address = "Dubrovnik, Croatia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.eacl-main.70",
doi = "10.18653/v1/2023.eacl-main.70",
pages = "993--1006",
abstract = "Most existing work on text simplification is limited to sentence-level inputs, with attempts to iteratively apply these approaches to document-level simplification failing to coherently preserve the discourse structure of the document. We hypothesise that by providing a high-level view of the target document, a simplification plan might help to guide generation. Building upon previous work on controlled, sentence-level simplification, we view a plan as a sequence of labels, each describing one of four sentence-level simplification operations (copy, rephrase, split, or delete). We propose a planning model that labels each sentence in the input document while considering both its context (a window of surrounding sentences) and its internal structure (a token-level representation). Experiments on two simplification benchmarks (Newsela-auto and Wiki-auto) show that our model outperforms strong baselines both on the planning task and when used to guide document-level simplification models.",
}
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<abstract>Most existing work on text simplification is limited to sentence-level inputs, with attempts to iteratively apply these approaches to document-level simplification failing to coherently preserve the discourse structure of the document. We hypothesise that by providing a high-level view of the target document, a simplification plan might help to guide generation. Building upon previous work on controlled, sentence-level simplification, we view a plan as a sequence of labels, each describing one of four sentence-level simplification operations (copy, rephrase, split, or delete). We propose a planning model that labels each sentence in the input document while considering both its context (a window of surrounding sentences) and its internal structure (a token-level representation). Experiments on two simplification benchmarks (Newsela-auto and Wiki-auto) show that our model outperforms strong baselines both on the planning task and when used to guide document-level simplification models.</abstract>
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%0 Conference Proceedings
%T Document-Level Planning for Text Simplification
%A Cripwell, Liam
%A Legrand, Joël
%A Gardent, Claire
%S Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
%D 2023
%8 May
%I Association for Computational Linguistics
%C Dubrovnik, Croatia
%F cripwell-etal-2023-document
%X Most existing work on text simplification is limited to sentence-level inputs, with attempts to iteratively apply these approaches to document-level simplification failing to coherently preserve the discourse structure of the document. We hypothesise that by providing a high-level view of the target document, a simplification plan might help to guide generation. Building upon previous work on controlled, sentence-level simplification, we view a plan as a sequence of labels, each describing one of four sentence-level simplification operations (copy, rephrase, split, or delete). We propose a planning model that labels each sentence in the input document while considering both its context (a window of surrounding sentences) and its internal structure (a token-level representation). Experiments on two simplification benchmarks (Newsela-auto and Wiki-auto) show that our model outperforms strong baselines both on the planning task and when used to guide document-level simplification models.
%R 10.18653/v1/2023.eacl-main.70
%U https://aclanthology.org/2023.eacl-main.70
%U https://doi.org/10.18653/v1/2023.eacl-main.70
%P 993-1006
Markdown (Informal)
[Document-Level Planning for Text Simplification](https://aclanthology.org/2023.eacl-main.70) (Cripwell et al., EACL 2023)
ACL
- Liam Cripwell, Joël Legrand, and Claire Gardent. 2023. Document-Level Planning for Text Simplification. In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, pages 993–1006, Dubrovnik, Croatia. Association for Computational Linguistics.