Dialogue Generation with GAN

Hui Su, Xiaoyu Shen, Pengwei Hu, Wenjie Li, Yun Chen

AAAI 2018 pp. 8163-8164

doi:10.1609/AAAI.V32I1.12158 /aaai/2018/su2018aaai-dialogue/

Abstract

This paper presents a Generative Adversarial Network (GAN) to model multiturn dialogue generation, which trains a latent hierarchical recurrent encoder-decoder simultaneously with a discriminative classifier that make the prior approximate to the posterior. Experiments show that our model achieves better results.

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Cite

Text

Su et al. "Dialogue Generation with GAN." AAAI Conference on Artificial Intelligence, 2018. doi:10.1609/AAAI.V32I1.12158

Markdown

[Su et al. "Dialogue Generation with GAN." AAAI Conference on Artificial Intelligence, 2018.](https://mlanthology.org/aaai/2018/su2018aaai-dialogue/) doi:10.1609/AAAI.V32I1.12158

BibTeX

@inproceedings{su2018aaai-dialogue,
  title     = {{Dialogue Generation with GAN}},
  author    = {Su, Hui and Shen, Xiaoyu and Hu, Pengwei and Li, Wenjie and Chen, Yun},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2018},
  pages     = {8163-8164},
  doi       = {10.1609/AAAI.V32I1.12158},
  url       = {https://mlanthology.org/aaai/2018/su2018aaai-dialogue/}
}