Papers by Haike Xu

1 papers
A Universal Discriminator for Zero-Shot Generalization (2023.acl-long)

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Challenge: Generative modeling has been the dominant approach for large-scale pretraining and zeroshot generalization.
Approach: They propose a discriminator that predicts whether a text sample comes from the true data distribution and which option has the highest probability of coming from the real data distribution.
Outcome: The proposed discriminative approach outperforms GANs on a number of NLP tasks by 16.0%, 7.8%, and 11.5% respectively.

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