Search Results for author: Zhongli Li

Found 11 papers, 10 papers with code

Towards Real-World Writing Assistance: A Chinese Character Checking Benchmark with Faked and Misspelled Characters

1 code implementation19 Nov 2023 Yinghui Li, Zishan Xu, Shaoshen Chen, Haojing Huang, Yangning Li, Yong Jiang, Zhongli Li, Qingyu Zhou, Hai-Tao Zheng, Ying Shen

To the best of our knowledge, Visual-C$^3$ is the first real-world visual and the largest human-crafted dataset for the Chinese character checking scenario.

Instance Segmentation for Chinese Character Stroke Extraction, Datasets and Benchmarks

1 code implementation25 Oct 2022 Lizhao Liu, Kunyang Lin, Shangxin Huang, Zhongli Li, Chao Li, Yunbo Cao, Qingyu Zhou

Moreover, there are no standardized benchmarks to provide a fair comparison between different stroke extraction methods, which, we believe, is a major impediment to the development of Chinese character stroke understanding and related tasks.

Font Generation Instance Segmentation +2

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

2 code implementations19 Oct 2022 Shirong Ma, Yinghui Li, Rongyi Sun, Qingyu Zhou, Shulin Huang, Ding Zhang, Li Yangning, Ruiyang Liu, Zhongli Li, Yunbo Cao, Haitao Zheng, Ying Shen

Extensive experiments and detailed analyses not only demonstrate that the training data constructed by our method effectively improves the performance of CGEC models, but also reflect that our benchmark is an excellent resource for further development of the CGEC field.

Grammatical Error Correction

AiM: Taking Answers in Mind to Correct Chinese Cloze Tests in Educational Applications

1 code implementation COLING 2022 Yusen Zhang, Zhongli Li, Qingyu Zhou, Ziyi Liu, Chao Li, Mina Ma, Yunbo Cao, Hongzhi Liu

To automatically correct handwritten assignments, the traditional approach is to use an OCR model to recognize characters and compare them to answers.

Optical Character Recognition (OCR)

Type-Driven Multi-Turn Corrections for Grammatical Error Correction

1 code implementation Findings (ACL) 2022 Shaopeng Lai, Qingyu Zhou, Jiali Zeng, Zhongli Li, Chao Li, Yunbo Cao, Jinsong Su

First, they simply mix additionally-constructed training instances and original ones to train models, which fails to help models be explicitly aware of the procedure of gradual corrections.

Data Augmentation Grammatical Error Correction +1

Improving BERT with Syntax-aware Local Attention

1 code implementation Findings (ACL) 2021 Zhongli Li, Qingyu Zhou, Chao Li, Ke Xu, Yunbo Cao

Pre-trained Transformer-based neural language models, such as BERT, have achieved remarkable results on varieties of NLP tasks.

Machine Translation Question Answering +3

Harvesting and Refining Question-Answer Pairs for Unsupervised QA

1 code implementation ACL 2020 Zhongli Li, Wenhui Wang, Li Dong, Furu Wei, Ke Xu

Our approach outperforms previous unsupervised approaches by a large margin and is competitive with early supervised models.

Few-Shot Learning Question Answering

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