Papers by Kuanning Wang

1 papers
DiffusionBERT: Improving Generative Masked Language Models with Diffusion Models (2023.acl-long)

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Challenge: Existing generative masked language models have a shared training objective, i.e., denoising.
Approach: They propose a noise schedule for the forward diffusion process that controls the degree of noise added at each step based on the information of each token.
Outcome: The proposed model improves on existing models in terms of perplexity and BLEU score.

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