2026
OTARo: Once Tuning for All Precisions Toward Robust On-Device LLMs
AAAI 2026technical
Large Language Models (LLMs) fine-tuning techniques not only improve the adaptability to diverse downstream tasks, but also mitigate adverse effects of model quantization. Despite this, conventional quantization suffers from its structural limitation that hinders flexibility during the fine-tuning