The paper proposes a new method for generating text that is both fluent and informative. The method is based on a novel neural network architecture that combines an autoregressive language model with a discriminative model. The autoregressive model generates text one word at a time, while the discriminative model scores the generated text and provides feedback to the autoregressive model. The paper demonstrates that the proposed method can generate text that is more fluent and informative than text generated by existing methods.
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