Towards Better Variational Encoder-Decoders in Seq2Seq Tasks
DOI:
https://doi.org/10.1609/aaai.v32i1.12157Abstract
Variational encoder-decoders have shown promising results in seq2seq tasks. However, the training process is known difficult to be controlled because latent variables tend to be ignored while decoding. In this paper, we thoroughly analyze the reason behind this training difficulty, compare different ways of alleviating it and propose a new framework that helps significantly improve the overall performance.
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Published
2018-04-29
How to Cite
Shen, X., & Su, H. (2018). Towards Better Variational Encoder-Decoders in Seq2Seq Tasks. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). https://doi.org/10.1609/aaai.v32i1.12157
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Student Abstract Track