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Research Review Notes

Summaries of academic research papers

Adversarial Learning for Neural Dialogue Generation


Idea

The authors formulate this dialogue model as a reinforcement learning problem. The network used is a Generative Adversarial Network. The discriminator objective is the same as a Turing test predictor i.e. classifies whether the dialogue response is human or machine-generated. The goal is to improve to improve the generator to the point where the discriminator has trouble distinguishing between human and machine-generated responses.

Method

Observations