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A Cross-Domain Transferable Neural Coherence Model

Coherence is an important aspect of text quality and is crucial for ensuring its readability. The proposed coherence model is simple in structure, yet it significantly outperforms previous state-of-art methods on a standard benchmark dataset on the Wall Street Journal corpus, as well as in multiple new challenging settings of transfer to unseen categories of discourse on Wikipedia articles.

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Cite this as

Peng Xu, Hamidreza Saghir, Jin Sung Kang, Teng Long, Avishek Joey Bose, Yanshuai Cao, Jackie Chi Kit Cheung (2025). Dataset: A Cross-Domain Transferable Neural Coherence Model. https://doi.org/10.57702/0sq8lnv8

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Additional Info

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Created January 2, 2025
Last update January 2, 2025
Defined In https://doi.org/10.48550/arXiv.1905.11912
Author Peng Xu
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Hamidreza Saghir
Jin Sung Kang
Teng Long
Avishek Joey Bose
Yanshuai Cao
Jackie Chi Kit Cheung
Homepage https://github.com/BorealisAI/cross_domain_coherence