Papers by Hsiu-Wen Li

1 papers
Improved Unsupervised Chinese Word Segmentation Using Pre-trained Knowledge and Pseudo-labeling Transfer (2023.emnlp-main)

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Challenge: Existing approaches to unsupervised Chinese word segmentation require multiple inferences to perform word segmenting.
Approach: They propose a method that integrates the segmentation signal from an unsupervised language model to a pre-trained BERT classifier under a pseudo-labeling framework.
Outcome: The proposed method achieves state-of-the-art performance on the eight UCWS tasks while significantly reducing training time compared to previous approaches.

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