Papers by Yanqiu Shao

3 papers
An Unsupervised Framework for Adaptive Context-aware Simplified-Traditional Chinese Character Conversion (2024.lrec-main)

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Challenge: Traditional Chinese characters are still widely used in many areas of China . traditional methods to convert between simplified characters are ineffective .
Approach: They propose an unsupervised adaptive context-aware conversion model that learns to convert between simplified and traditional Chinese characters under a denoising auto-encoder framework.
Outcome: The proposed model outperforms strong unsupervised baselines and yields better conversion result for one-to-many cases.
Unsupervised Chinese Word Segmentation with BERT Oriented Probing and Transformation (2022.findings-acl)

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Challenge: Existing methods for unsupervised Chinese word segmentation exploit shallow semantic information, which can miss important context.
Approach: They propose to take advantage of deep contextual semantic information with a self-training manner to transform it into explicit word segmentation ability.
Outcome: The proposed approach achieves state-of-the-art F1 score on two CWS benchmark datasets.
Enhancing Discourse Dependency Parsing with Sentence Dependency Parsing: A Unified Generative Method Based on Code Representation (2024.findings-emnlp)

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Challenge: Existing annotation resources for Discourse Dependency Parsing tasks are limited due to their complexity and annotation schema differences.
Approach: They propose a code-based unified dependency parsing method that uses code to model dependency parses under different annotation schemas.
Outcome: The proposed method improves on two Chinese DDP tasks.

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