Papers by Alex Smola

1 papers
A Cheaper and Better Diffusion Language Model with Soft-Masked Noise (2023.emnlp-main)

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Challenge: Existing diffusion models have limitations in modeling discrete data, e.g., languages . we present a novel diffusion model for language modeling inspired by linguistic features in languages based on iterative denoising .
Approach: They propose a method that iteratively denoises and adds corruptions to the textual data through soft-masking to better noise it.
Outcome: The proposed model achieves better generation quality and lower training cost than current models with better performance.

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