A Note on LoRA
<|reference_start|>A Note on LoRA: LoRA (Low-Rank Adaptation) has emerged as a preferred method for efficiently adapting Large Language Models (LLMs) with remarkable simplicity and efficacy. This note extends the original LoRA paper by offering new perspectives that were not initially discussed and presents a series of insights for deploying LoRA at scale. Without introducing new experiments, we aim to improve the understanding and application of LoRA.<|reference_end|>
@article{fomenko2024a,
    title={A Note on LoRA},
    author={Vlad Fomenko, Han Yu, Jongho Lee, Stanley Hsieh, Weizhu Chen},
    journal={arXiv preprint arXiv:2404.05086},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.05086},
    primaryClass={cs.LG cs.AI cs.CL}
}