论文笔记BERT: Bidirectional Encoder Representations from Transformers

时间 2020-12-30

标签 NLP 人工智能繁體版

原文原文链接

1 简介本文根据2019年《BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding》翻译总结的。 BERT: Bidirectional Encoder Representations from Transformers. 应用预训练模型于下游任务有两种策略，分别是feature-based

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1. LXMERT: Learning Cross-Modality Encoder Representations from Transformers 论文笔记
2. Bert：论文阅读-BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
3. BERT: Bidirectional Encoder Representations from Transformers双向Transformer用于语言模型 NAACL 2018
4. 论文笔记：NAACL-HLT 2018 BERT Pre-training of Deep Bidirectional Transformers for
5. 论文阅读笔记：BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
6. 论文笔记《BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding》
7. BERT论文阅读笔记
8. 从Transformers学习跨模态编码器表示《LXMERT: Learning Cross-Modality Encoder Representations from Transformers》
9. 论文学习《BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding》
10. 文献记录－BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

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