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cs.LG2026
Optimizers for Diffusion Models: A Controlled Benchmark
Arman Bolatov, Egor Shulgin, David Li +6
Discrete diffusion models now match autoregressive language models on several benchmarks, while the question of how best to train them has received far less attention: the optimize…
cs.LG2026
Deriving Hyperparameter Scaling Laws via Modern Optimization Theory
Egor Shulgin, Dimitri von Rütte, Tianyue H. Zhang +3
Hyperparameter transfer has become an important component of modern large-scale training recipes. Existing methods, such as muP, primarily focus on transfer between model sizes, wi…