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今天的主题是：BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Summary

The paper proposes a new language representation model called BERT (Bidirectional Encoder Representations from Transformers), which is designed to learn deep bidirectional representations from unlabeled text. Unlike prior models, BERT jointly conditions on both left and right context in all layers, which allows it to better understand the relationships between sentences. The paper demonstrates BERT's effectiveness on 11 natural language processing tasks, achieving state-of-the-art results and outperforming many task-specific architectures. BERT is conceptually simple and empirically powerful, and its code and pre-trained models are publicly available.

原文链接：arxiv.org