Papers by Vijil Chenthamarakshan

1 papers
Learning Implicit Text Generation via Feature Matching (2020.acl-main)

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Challenge: Generative feature matching networks are an approach for training implicit generative models for images . a novel formulation of GFMN for unconditional sequence generation is proposed .
Approach: They propose a new GFMN formulation that performs token level feature matching on pre-trained neural networks.
Outcome: The proposed method outperforms adversarial approaches for text generation and style transfer.

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