GPT-3：Language Models are Few-Shot Learners 論文解讀
paper鏈接：https://arxiv.org/abs/2005.14165 github鏈接：https://github.com/openai/gpt-3 摘要 通過對大量文本進行預訓練，然後對特定任務進行微調，最近的工作證明了在許多NLP任務和基準方面的巨大收穫。儘管在結構上通常與任務無關，但是此方法仍然需要特定於任務的微調數據集，該數據集包含成千上萬個示例。相比之下，人類通常只能通過幾
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相關文章
- 1. GPT2--Language Models are Unsupervised Multitask Learners
- 2. GPT-3：Language Models are Few-Shot Learners 論文解讀
- 3. GPT2.0 Language Models are Unsupervised Multitask Learners 論文解讀
- 4. 論文分享 -- > NLP -- > Language Models are Unsupervised Multitask Learners
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- 8. OpenAI GPT-2語言模型是非監督多任務學習器 Language Models are Unsupervised Multitask Learners
- 9. 論文閱讀：《A Primer on Neural Network Models for Natural Language Processing》（一）
- 10. 論文閱讀：Generating Abstractive Summaries with Finetuned Language Models