【深度學習NLP論文筆記】《Visualizing and Understanding Neural Models in NLP》
1 Introduction 神經網絡對於NLP任務的可解釋性很差。深度學習模型主要是基於word embedding詞嵌入（比如low-dimensional，continuous，real-valued vector）。在本文中，我們使用傳統方法，比如representation plotting，並使用一些簡單策略來評估一個神經元（neural unit）對於語義構建（meaning com
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相關文章
- 1. 【深度學習NLP論文筆記】《Understanding Neural Networks through Representation Erasure》
- 2. 論文筆記Visualizing and understanding convolutional networks
- 3. 論文筆記：Visualizing and Understanding Convolutional Networks
- 4. 【論文閱讀筆記】Analyzing and Interpreting Convolutional Neural Networks in NLP
- 5. Understanding Convolutional Neural Networks for NLP
- 6. [轉] Understanding Convolutional Neural Networks for NLP
- 7. 論文閱讀筆記（四十二）：Visualizing and Understanding Convolutional Networks
- 8. Understanding and Visualizing Convolutional Neural Networks
- 9. visualizing and understanding convolution network論文
- 10. 【深度學習NLP論文筆記】《Interpretable Adversarial Perturbation in Input Embedding Space for Text》