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cs.LG2026
LoRA-generating hypernetworks for efficient on-device LLM generative personalization
Sean Augenstein, Li Ding, Jihwan Lee +2
On-device large language models (`LLMs'), e.g. running on mobile phones, are ripe for improvement via personalization. The limited compute resources of mobile devices impose limits…
cs.CL2026
Mixture of Training: Recombining Small-Scale Scaffolded Pretraining Runs into a Larger Language Model
Mohammed Sabry, Sean Augenstein, Keith Rush +1
We ask whether language-model pre-training can be decomposed into smaller, independently trainable jobs that can later be recomposed into a coherent larger model. We introduce Mixt…