Attention-based Encoder-Decoder Neural Network
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A Attention-based Encoder-Decoder Neural Network is an Encoder-Decoder Neural Network that includes an Attention Mechanism.
- AKA: Attention-based Encoder-Decoder Neural Network.
- Context:
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- Example(s):
- Counter-Example(s):
- See: Content-Based Attention Network, Neural NLP.
References
2016a
- (Schmaltz et al., 2016) ⇒ Allen Schmaltz, Yoon Kim, Alexander M Rush, and Stuart Shieber. (2016). “Sentence-Level Grammatical Error Identification As Sequence-to-Sequence Correction.” In: Proceedings of the 11th Workshop on Innovative Use of NLP for Building Educational Applications.
- QUOTE: We demonstrate that an attention-based encoder-decoder model can be used for sentence-level grammatical error identification for the Automated Evaluation of Scientific Writing (AESW) Shared Task 2016. …
2016b
- (Xie et al., 2016) ⇒ Ziang Xie, Anand Avati, Naveen Arivazhagan, Dan Jurafsky, and Andrew Y. Ng. (2016). “Neural Language Correction with Character-Based Attention.” In: CoRR, abs/1603.09727.
2015
- (Bahdanau et al., 2015) ⇒ Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. (2015). “Neural Machine Translation by Jointly Learning to Align and Translate.” In: Proceedings of the Third International Conference on Learning Representations, (ICLR-2015).