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Dan Chen

1 accepted papers

2024

MiLoRA: Efficient Mixture of Low-Rank Adaptation for Large Language Models Fine-tuning

EMNLP 2024finding

Low-rank adaptation (LoRA) and its mixture-of-experts (MOE) variants are highly effective parameter-efficient fine-tuning (PEFT) methods. However, they introduce significant latency in multi-tenant settings due to the LoRA modules and MOE routers added to multiple linear modules in the Transformer l…