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20212026
most citedOn the (In)Effectiveness of Large Language Models for Chinese Text Correction

17 citations · 57 across the 17 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

cs.CL2022★ 1 cited

Towards Attribute-Entangled Controllable Text Generation: A Pilot Study of Blessing Generation

Shulin Huang, Shirong Ma, Yinghui Li +4

Controllable Text Generation (CTG) has obtained great success due to its fine-grained generation ability obtained by focusing on multiple attributes. However, most existing CTG res…

cs.CL2022★ 4 cited

Focus Is What You Need For Chinese Grammatical Error Correction

Jingheng Ye, Yinghui Li, Shirong Ma +3

Chinese Grammatical Error Correction (CGEC) aims to automatically detect and correct grammatical errors contained in Chinese text. In the long term, researchers regard CGEC as a ta…

cs.CL2022★ 1 cited

Linguistic Rules-Based Corpus Generation for Native Chinese Grammatical Error Correction

Shirong Ma, Yinghui Li, Rongyi Sun +9

Chinese Grammatical Error Correction (CGEC) is both a challenging NLP task and a common application in human daily life. Recently, many data-driven approaches are proposed for the…

cs.CL2022★ 2 cited

Learning from the Dictionary: Heterogeneous Knowledge Guided Fine-tuning for Chinese Spell Checking

Yinghui Li, Shirong Ma, Qingyu Zhou +7

Chinese Spell Checking (CSC) aims to detect and correct Chinese spelling errors. Recent researches start from the pretrained knowledge of language models and take multimodal inform…

cs.CL2022

Contextual Similarity is More Valuable than Character Similarity: An Empirical Study for Chinese Spell Checking

Ding Zhang, Yinghui Li, Qingyu Zhou +4

Chinese Spell Checking (CSC) task aims to detect and correct Chinese spelling errors. Recently, related researches focus on introducing character similarity from confusion set to e…