@inproceedings{vasquez-rodriguez-etal-2023-document,
title = "Document-level Text Simplification with Coherence Evaluation",
author = "V{\'a}squez-Rodr{\'\i}guez, Laura and
Shardlow, Matthew and
Przyby{\l}a, Piotr and
Ananiadou, Sophia",
editor = "{\v{S}}tajner, Sanja and
Saggio, Horacio and
Shardlow, Matthew and
Alva-Manchego, Fernando",
booktitle = "Proceedings of the Second Workshop on Text Simplification, Accessibility and Readability",
month = sep,
year = "2023",
address = "Varna, Bulgaria",
publisher = "INCOMA Ltd., Shoumen, Bulgaria",
url = "https://aclanthology.org/2023.tsar-1.9",
pages = "85--101",
abstract = "We present a coherence-aware evaluation of document-level Text Simplification (TS), an approach that has not been considered in TS so far. We improve current TS sentence-based models to support a multi-sentence setting and the implementation of a state-of-the-art neural coherence model for simplification quality assessment. We enhanced English sentence simplification neural models for document-level simplification using 136,113 paragraph-level samples from both the general and medical domains to generate multiple sentences. Additionally, we use document-level simplification, readability and coherence metrics for evaluation. Our contributions include the introduction of coherence assessment into simplification evaluation with the automatic evaluation of 34,052 simplifications, a fine-tuned state-of-the-art model for document-level simplification, a coherence-based analysis of our results and a human evaluation of 300 samples that demonstrates the challenges encountered when moving towards document-level simplification.",
}
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%0 Conference Proceedings
%T Document-level Text Simplification with Coherence Evaluation
%A Vásquez-Rodríguez, Laura
%A Shardlow, Matthew
%A Przybyła, Piotr
%A Ananiadou, Sophia
%Y Štajner, Sanja
%Y Saggio, Horacio
%Y Shardlow, Matthew
%Y Alva-Manchego, Fernando
%S Proceedings of the Second Workshop on Text Simplification, Accessibility and Readability
%D 2023
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F vasquez-rodriguez-etal-2023-document
%X We present a coherence-aware evaluation of document-level Text Simplification (TS), an approach that has not been considered in TS so far. We improve current TS sentence-based models to support a multi-sentence setting and the implementation of a state-of-the-art neural coherence model for simplification quality assessment. We enhanced English sentence simplification neural models for document-level simplification using 136,113 paragraph-level samples from both the general and medical domains to generate multiple sentences. Additionally, we use document-level simplification, readability and coherence metrics for evaluation. Our contributions include the introduction of coherence assessment into simplification evaluation with the automatic evaluation of 34,052 simplifications, a fine-tuned state-of-the-art model for document-level simplification, a coherence-based analysis of our results and a human evaluation of 300 samples that demonstrates the challenges encountered when moving towards document-level simplification.
%U https://aclanthology.org/2023.tsar-1.9
%P 85-101
Markdown (Informal)
[Document-level Text Simplification with Coherence Evaluation](https://aclanthology.org/2023.tsar-1.9) (Vásquez-Rodríguez et al., TSAR-WS 2023)
ACL
- Laura Vásquez-Rodríguez, Matthew Shardlow, Piotr Przybyła, and Sophia Ananiadou. 2023. Document-level Text Simplification with Coherence Evaluation. In Proceedings of the Second Workshop on Text Simplification, Accessibility and Readability, pages 85–101, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.