《Fluency Boost Learning and Inference for Neural Grammatical Error Correction》论文总结
今天看到微软亚洲研究院的一篇论文，通过Fluency boost learning提升模型性能，论文地址为: Fluency Boost Learning and Inference for Neural Grammatical Error Correction，有兴趣的同学可以去下载看看。在此我总结了一下这篇论文。 核心思想 这篇论文的核心思想其实很简单，就是通过有效地增加训练数据，来使模型的推
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相关文章
- 1. A Simple but Effective Classification Model for Grammatical Error Correction
- 2. embedding entities and relations for learning and inference knowledge base
- 3. 《Enhanced LSTM for Natural Language Inference》论文总结
- 4. 论文阅读——Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference
- 5. 【论文阅读】Neural Language Correction with Character-Based Attention
- 6. 论文笔记 Joint Inference of Reward Machines and Policies for Reiforcement Learning
- 7. Neural Architecture Search with Reinforcement Learning论文总结
- 8. Classification and inference with machine learning
- 9. 《Wide & Deep Learning for Recommender Systems》论文总结
- 10. 论文《Convolutional Neural Networks for Sentence Classification》总结