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Shaoyuan Chen

1 accepted papers

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

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