10 citations · 36 across the 12 of their papers we have counts for
3 papers · 1 filter
What happens when nanochat meets DiLoCo?
Alexander Acker, Soeren Becker, Sasho Nedelkoski +3
Although LLM training is typically centralized with high-bandwidth interconnects and large compute budgets, emerging methods target communication-constrained training in distribute…
Comparative Analysis of Large Language Models for the Machine-Assisted Resolution of User Intentions
Justus Flerlage, Alexander Acker, Odej Kao
Large Language Models (LLMs) have emerged as transformative tools for natural language understanding and user intent resolution, enabling tasks such as translation, summarization,…
Distributed Low-Communication Training with Decoupled Momentum Optimization
Sasho Nedelkoski, Alexander Acker, Odej Kao +2
The training of large models demands substantial computational resources, typically available only in data centers with high-bandwidth interconnects. However, reducing the reliance…