Research Papers Institution
A research group working on parameter-efficient fine-tuning and infrastructure for personalized models at scale.
Fine-Tuning & Adaptation · Mind Lab
MinT keeps one frontier base model resident and swaps only LoRA adapters, cutting the model-handoff step by 18.3x on a 4B dense model and 2.85x on a 30B MoE, while addressing million-scale adapter catalogs.
Fine-Tuning & Adaptation · Mind Lab
A position paper reframing LoRA adapters as persistent personal state, not a cheap full-finetune substitute, across three axes: scale up the base, scale down the adapter, scale out to millions, plus a serving stack MinT.