文献阅读笔记—Improving Language Understanding by Generative Pre-Training
迁移学习在nlp领域的应用之pretrain language representation，四连载，建议按顺序看，看完对该方向一定会非常清楚的！ （一）ELMO：Deep contextualized word representations （二）Universal Language Model Fine-tuning for Text Classification （三）openAI GPT
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相关文章
- 1. Improving Language Understanding by Generative Pre-Training阅读笔记
- 2. 文献阅读笔记：XLNet: Generalized Autoregressive Pretraining for Language Understanding
- 3. 【论文笔记】Improving Language Understanding by Generative Pre-Training
- 4. GPT模型：Improving Language Understanding by Generative Pre-Training
- 5. 文献阅读笔记：NEZHA(Neural Contextualized Representation for Chinese Language Understanding)
- 6. 深度学习 -- > NLP -- >Improving Language Understanding by Generative Pre-Training
- 7. 【论文阅读笔记】Cross-lingual Language Model Pretraining
- 8. Multi-Task Deep Neural Networks for Natural Language Understanding阅读笔记
- 9. 文献阅读：Improving neural networks by preventing co-adaptation of feature detectors
- 10. Generative Adversarial Networks: An Overview文献阅读笔记