GPT-3：Language Models are Few-Shot Learners 论文解读

时间 2020-07-23

标签 gpt language models shot learners 论文解读繁體版

原文原文链接

paper连接：https://arxiv.org/abs/2005.14165git github连接：https://github.com/openai/gpt-3github 摘要经过对大量文本进行预训练，而后对特定任务进行微调，最近的工做证实了在许多NLP任务和基准方面的巨大收获。尽管在结构上一般与任务无关，可是此方法仍然须要特定于任务的微调数据集，该数据集包含成千上万个示例。相比之下，

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1. GPT2--Language Models are Unsupervised Multitask Learners
2. GPT-3：Language Models are Few-Shot Learners 论文解读
3. GPT2.0 Language Models are Unsupervised Multitask Learners 论文解读
4. 论文分享 -- > NLP -- > Language Models are Unsupervised Multitask Learners
5. Big Self-Supervised Models are Strong Semi-Supervised Learners论文研读
6. EMNLP2020 | Language Model精选论文解读
7. 【论文笔记】Character-Aware Neural Language Models
8. OpenAI GPT-2语言模型是非监督多任务学习器 Language Models are Unsupervised Multitask Learners
9. 论文阅读：《A Primer on Neural Network Models for Natural Language Processing》（一）
10. 论文阅读：Generating Abstractive Summaries with Finetuned Language Models

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