基于注意力机制的模型在自然语言中的具体应用及其参考文献

1. 机器翻译：Bahdanau, D., Cho, K., & Bengio, Y. (2015). Neural machine translation by jointly learning to align and translate. Proceedings of the International Conference on Learning Representations (ICLR).

2. 文本摘要：See, A., Liu, P. J., & Manning, C. D. (2017). Get to the point: Summarization with pointer-generator networks. Proceedings of the Association for Computational Linguistics (ACL).

3. 问答系统：Xiong, C., Zhong, V., & Socher, R. (2016). Dynamic coattention networks for question answering. Proceedings of the International Conference on Learning Representations (ICLR).

4. 对话生成：Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., ... & Polosukhin, I. (2017). Attention is all you need. Proceedings of the Advances in Neural Information Processing Systems (NIPS).

以上是常见的基于注意力机制的模型在自然语言处理中的应用及其参考文献。