GPT-3是由OpenAI开发的自然语言处理模型，于2020年发布。以下是相关论文列表：
Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., … & Amodei, D. (2020). Language models are few-shot learners. arXiv preprint arXiv:2005.14165.
Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., & Sutskever, I. (2019). Language models are unsupervised multitask learners. OpenAI blog, 1(8), 9.
Radford, A., Narasimhan, K., Salimans, T., & Sutskever, I. (2018). Improving language understanding by generative pre-training. URL https://s3-us-west-2. amazonaws. com/openai-assets/researchcovers/languageunsupervised/language_understanding_paper. pdf.
Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., … & Amodei, D. (2020). A large-scale study of representation learning with the transformer model. arXiv preprint arXiv:2012.15723.
其中，Brown等人在第一篇论文中介绍了GPT-3的设计和实现，提出了“few-shot learning”的思路，并通过大量实验验证了该模型的优异表现；而Radford等人在第二、三篇论文中提出了基于无监督学习的预训练方法，并演示了其在多任务学习和生成领域的应用；最后一篇论文则是对GPT-3模型进行了更深入的实验研究，探究了其表示学习能力和泛化性能等方面的特点。