Seq2seq
2020/12/04
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https://pixabay.com/zh/photos/artwork-hue-lighting-lamps-3719514/
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◎ Abstract
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◎ Introduction
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本論文要解決(它之前研究)的(哪些)問題(弱點)?
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# History DL。
說明:
在非整句讀完就開始輸出的情況下,有斷章取義的缺點。
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# RCTM。
說明:
Encoder 端採用一維卷積,但不像後續的 ConvS2S 有加入時間的資訊。
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◎ Method
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解決方法?
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# Seq2seq 1。
說明:
整句讀完再開始解碼。
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具體細節?
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◎ Result
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本論文成果。
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◎ Discussion
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本論文與其他論文(成果或方法)的比較。
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成果比較。
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方法比較。
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◎ Conclusion
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◎ Future Work
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後續相關領域的研究。
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後續延伸領域的研究。
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◎ References
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# RCTM。被引用 1137 次。
Kalchbrenner, Nal, and Phil Blunsom. "Recurrent continuous translation models." Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing. 2013.
https://www.aclweb.org/anthology/D13-1176.pdf
# Seq2seq 1。被引用 12676 次。
Sutskever, Ilya, Oriol Vinyals, and Quoc V. Le. "Sequence to sequence learning with neural networks." Advances in neural information processing systems. 2014.
http://papers.nips.cc/paper/5346-sequence-to-sequence-learning-with-neural-networks.pdf
# Seq2seq 2。被引用 11284 次。
Cho, Kyunghyun, et al. "Learning phrase representations using RNN encoder-decoder for statistical machine translation." arXiv preprint arXiv:1406.1078 (2014).
https://arxiv.org/pdf/1406.1078.pdf
# Paragraph2vec。被引用 6763 次。
Le, Quoc, and Tomas Mikolov. "Distributed representations of sentences and documents." International conference on machine learning. 2014.
http://proceedings.mlr.press/v32/le14.pdf
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# History DL。
Alom, Md Zahangir, et al. "The history began from alexnet: A comprehensive survey on deep learning approaches." arXiv preprint arXiv:1803.01164 (2018).
https://arxiv.org/ftp/arxiv/papers/1803/1803.01164.pdf
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