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- W3200202382 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 An-chiBERT, 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.
- W3200202382 created "2021-09-27" @default.
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- W3200202382 date "2021-07-18" @default.
- W3200202382 modified "2023-10-12" @default.
- W3200202382 title "AnchiBERT: A Pre-Trained Model for Ancient Chinese Language Understanding and Generation" @default.
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- W3200202382 doi "https://doi.org/10.1109/ijcnn52387.2021.9534342" @default.
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