MaskGAN Network Model

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A MaskGAN Network Model is a Generative Adversarial Network that fills-in missing text conditioned on context-based masked sequences.



References

2018

2018 MaskGANBetterTextGenerationviaF Fig1.png
Figure 1: seq2seq generator architecture. Blue boxes represent known tokens and purple boxes are imputed tokens. We demonstrate a sampling operation via the dotted line. The encoder reads in a masked sequence, where masked tokens are denoted by an underscore, and then the decoder imputes the missing tokens by using the encoder hidden states. In this example, the generator should fill in the alphabetical ordering, (a, b, c, d, e).

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