《Attentional Encoder Network for Targeted Sentiment Classification》
這篇paper，我認爲是BERT的又一篇跟風之作。 裏頭提到， 1. 用RNN不用LSTM的理由，LSTM有遺忘機制，但是帶來了一個負面效果，它可能會需要更多的訓練數據。 2. label unreliability issus, 標籤可可靠問題。更少的依靠標籤可靠性問題。 # introspective 好反省的。內省。 # interactive 相互作用 帶來了目標和內容單詞的內
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相關文章
- 1. 《Attentional Encoder Network for Targeted Sentiment Classification》
- 2. Linguistically Regularized LSTMs for Sentiment Classification
- 3. 《Effective LSTMs for Target-Dependent Sentiment Classification》
- 4. Aspect Level Sentiment Classification with Deep Memory Network筆記
- 5. Hierarchical Attention Network for Document Classification閱讀筆記
- 6. Document Modeling with Gated Recurrent Neural Network for Sentiment Classification 論文閱讀筆記
- 7. 【論文閱讀筆記】Document Modeling with Gated Recurrent Neural Network for Sentiment Classification
- 8. 《Attention-based LSTM for Aspect-level Sentiment Classification》
- 9. 2017acl---Linguistically Regularized LSTM for Sentiment Classification筆記
- 10. VistaNet: Visual Aspect Attention Network for Multimodal Sentiment Analysis 論文解讀