GPT2--Language Models are Unsupervised Multitask Learners
Abstact GPT2的核心思想就是认为能够用无监督的预训练模型去作有监督任务。 Introduction： 典型应用：最著名的语言模型就是手机上面的输入法，根据当前输入词推荐下一个词 目标上想构造一个通用的NLP模型，能够执行不少任务，不须要为每一个任务手动建立和标记数据集 多任务学习：把多个相关的任务放在一块儿学习，同时学习多个任务。 基于共享表示，把多个相关的任务放在一块儿学习的机器学习方
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相关文章
- 1. 论文分享 -- > NLP -- > Language Models are Unsupervised Multitask Learners
- 2. GPT2.0 Language Models are Unsupervised Multitask Learners 论文解读
- 3. OpenAI GPT-2语言模型是非监督多任务学习器 Language Models are Unsupervised Multitask Learners
- 4. GPT-3：Language Models are Few-Shot Learners 论文解读
- 5. Big Self-Supervised Models are Strong Semi-Supervised Learners论文研读
- 6. Mean teachers are better role models
- 7. Unsupervised Deep Structured Semantic Models for Commonsense Reasoning
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- 9. Distral: Robust multitask reinforcement learning.
- 10. 【论文阅读笔记】Recursive Unsupervised Learning of Finite Mixture Models