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--- |
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language: zh |
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pipeline_tag: fill-mask |
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tags: |
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- bert |
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license: apache-2.0 |
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--- |
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## Chinese Kowledge-enhanced BERT (CKBERT) |
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Knowledge-enhanced pre-trained language models (KEPLMs) improve context-aware representations via learning from structured relations in knowledge graphs, and/or linguistic knowledge from syntactic or dependency analysis. Unlike English, there is a lack of high-performing open-source Chinese KEPLMs in the natural language processing (NLP) community to support various language understanding applications. |
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For Chinese natural language processing, we provide three **Chinese Kowledge-enhanced BERT (CKBERT)** models named **pai-ckbert-bert-zh**, **pai-ckbert-large-zh** and **pai-ckbert-huge-zh**, from our **EMNLP 2022** paper named **Revisiting and Advancing Chinese Natural Language Understanding with Accelerated Heterogeneous Knowledge Pre-training**. |
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This repository is developed based on the EasyNLP framework: [https://github.com/alibaba/EasyNLP](https://github.com/alibaba/EasyNLP ) |
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## Citation |
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If you find the resource is useful, please cite the following papers in your work. |
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- For the EasyNLP framework: |
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``` |
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@article{easynlp, |
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title = {EasyNLP: A Comprehensive and Easy-to-use Toolkit for Natural Language Processing}, |
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publisher = {arXiv}, |
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author = {Wang, Chengyu and Qiu, Minghui and Zhang, Taolin and Liu, Tingting and Li, Lei and Wang, Jianing and Wang, Ming and Huang, Jun and Lin, Wei}, |
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url = {https://arxiv.org/abs/2205.00258}, |
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year = {2022} |
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} |
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``` |
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- For DKPLM: |
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``` |
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@article{ckbert, |
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title = {Revisiting and Advancing Chinese Natural Language Understanding with Accelerated Heterogeneous Knowledge Pre-training}, |
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author = {Zhang, Taolin and Dong, Junwei and Wang, Jianing and Wang, Chengyu and Wang, An and Liu, Yinghui and Huang, Jun and Li, Yong and He, Xiaofeng}, |
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publisher = {EMNLP}, |
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year = {2022} |
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} |
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``` |
