SynPro uses RL-optimized rephrasing and reformatting of organic data to generate synthetic pretraining tokens that deliver 3.7-5.2x the effective learning of simple repetition and can exceed training on unique data at 1.1B scale.
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Primal-dual guided decoding casts constrained discrete diffusion as a KL-regularized optimization solved online with adaptive Lagrangian multipliers to satisfy constraints while staying close to the unconstrained model distribution.
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Generating Pretraining Tokens from Organic Data for Data-Bound Scaling
SynPro uses RL-optimized rephrasing and reformatting of organic data to generate synthetic pretraining tokens that deliver 3.7-5.2x the effective learning of simple repetition and can exceed training on unique data at 1.1B scale.
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Primal-Dual Guided Decoding for Constrained Discrete Diffusion
Primal-dual guided decoding casts constrained discrete diffusion as a KL-regularized optimization solved online with adaptive Lagrangian multipliers to satisfy constraints while staying close to the unconstrained model distribution.