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AAAI 2018

Towards Better Variational Encoder-Decoders in Seq2Seq Tasks

Short Paper Student Abstract Track Artificial Intelligence

Abstract

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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Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
711320136622713459
v2026.09.13