MetaEx-GAN: Meta Exploration to Improve Natural Language Generation via Generative Adversarial Networks-Reference-Cited by-同舟云学术

MetaEx-GAN: Meta Exploration to Improve Natural Language Generation via Generative Adversarial Networks

Author:

Chuang Yun-Yen¹^ORCID,Hsu Hung-Min²^ORCID,Lin Kevin²^ORCID,Chang Ray-I.³^ORCID,Lee Hung-Yi¹^ORCID

Affiliation:

1. Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan

2. Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA

3. Department of Engineering Science and Ocean Engineering, National Taiwan University, Taipei, Taiwan

Funder

National Science and Technology Council, R.O.C.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Acoustics and Ultrasonics,Computer Science (miscellaneous),Computational Mathematics

Link

Reference36 articles.

1. GANs for sequences of discrete elements with the Gumbel-softmax distribution;kusner,2016

2. TaylorGAN: Neighbor-augmented policy update towards sample-efficient natural language generation;lin;Proc Int Conf Adv Neural Inf Process Syst,0

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