Scaling Categorical Flow Maps
Continuous diffusion and flow matching models could represent a powerful alternative to autoregressive approaches for language modelling (LM), as they unlock a host of advantages currently reserved for continuous modalities, including accelerated sampling and tilting. Recently, several works have demonstrated the possibility of generating discrete data continuously by a simple flow matching process between a...
What happened
Continuous diffusion and flow matching models could represent a powerful alternative to autoregressive approaches for language modelling (LM), as they unlock a host of advantages currently reserved for continuous modalities, including accelerated sampling and tilting. Recently, several works have demonstrated the possibility of generating discrete data continuously by a simple flow matching process between a...
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1 reports · 1 original report · 1 independent
- Apple Machine Learning ResearchPrimary source · Supports · EN · 100%Scaling Categorical Flow Maps ↗
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- Scaling Categorical Flow Maps Observed
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