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Low-rank Gaussian perturbations

topic1 events
papersSEP 12 04:00 UTC

EGGROLL Unrolled: Study Examines Low-Rank Evolution Strategies at Scale

A new arXiv paper analyzes EGGROLL, a method that makes evolution strategies viable for large language models by swapping dense Gaussian weight perturbations for low-rank Gaussian products, frequently of rank one. While this substitution reduces computation, the authors note it imposes severe geometric constraints on the perturbation space. The work aims to explain those limitations and propose improvements for scaling the approach.

evolution-strategies/llm-training/optimization/research