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Plaid

model1 events
papersSEP 11 04:00 UTC

Study Argues Continuous Diffusion Can Scale Competitively for Language Modeling

A new arXiv paper revisits Plaid, a likelihood-based continuous diffusion model for text, to test the assumption that continuous diffusion scales worse than discrete alternatives. The authors report that with the right design, continuous diffusion can match discrete diffusion at scale. The work is a replacement version of a cross-listed machine learning preprint.

diffusion/language-models/scaling/research