Papers by Xiongfeng Xiao

1 papers
Refining Corpora from a Model Calibration Perspective for Chinese Spelling Correction (2024.findings-acl)

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Challenge: Chinese Spelling Correction (CSC) lacks large-scale high-quality corpora due to labor-intensive labeling of spelling errors in real-life writing or typing scenarios.
Approach: They propose to use OCR/ASR-based generation to refine Chinese Spelling Correction models on random replacement-based corpora and filter them based on prediction confidence.
Outcome: The proposed model outperforms existing models on three widely-used benchmarks while significantly alleviating over-correction.

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