Character-Aware Neural Networks for Word-Level Prediction: Do They Discover Linguistic Rules?

Character-level features are currently used in different neural network-based natural language processing algorithms. However, little is known about the character-level patterns those models learn. Moreover, models are often compared only quantitatively while a qualitative analysis is missing. In this paper, we investigate which character-level patterns neural networks learn and if those patterns coincide with manually-defined word segmentations and annotations.

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Fréderic Godin, Kris Demuynck, Joni Dambre, Wesley De Neve, Thomas Demeester (2024). Dataset: Character-Aware Neural Networks for Word-Level Prediction: Do They Discover Linguistic Rules?. https://doi.org/10.57702/97i8anr2

DOI retrieved: December 16, 2024

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Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.1808.09551
Author Fréderic Godin
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Kris Demuynck
Joni Dambre
Wesley De Neve
Thomas Demeester
Homepage https://github.com/FredericGodin/ContextualDecomposition-NLP