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• W3089207345 abstract "Ancient Chinese is the essence of Chinese culture. There are several natural language processing tasks of ancient Chinese domain, such as ancient-modern Chinese translation, poem generation, and couplet generation. Previous studies usually use the supervised models which deeply rely on parallel data. However, it is difficult to obtain large-scale parallel data of ancient Chinese. In order to make full use of the more easily available monolingual ancient Chinese corpora, we release AnchiBERT, a pre-trained language model based on the architecture of BERT, which is trained on large-scale ancient Chinese corpora. We evaluate AnchiBERT on both language understanding and generation tasks, including poem classification, ancient-modern Chinese translation, poem generation, and couplet generation. The experimental results show that AnchiBERT outperforms BERT as well as the non-pretrained models and achieves state-of-the-art results in all cases." @default.
• W3089207345 created "2020-10-01" @default.
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• W3089207345 date "2020-09-23" @default.
• W3089207345 modified "2023-09-27" @default.
• W3089207345 title "AnchiBERT: A Pre-Trained Model for Ancient ChineseLanguage Understanding and Generation" @default.
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• W3089207345 doi "https://doi.org/10.48550/arxiv.2009.11473" @default.
• W3089207345 hasPublicationYear "2020" @default.
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