Navigating the Landscape of Large Language Models: A Comprehensive Review and Analysis of Paradigms and Fine-Tuning Strategies
<|reference_start|>Navigating the Landscape of Large Language Models: A Comprehensive Review and Analysis of Paradigms and Fine-Tuning Strategies: With the surge of ChatGPT,the use of large models has significantly increased,rapidly rising to prominence across the industry and sweeping across the internet. This article is a comprehensive review of fine-tuning methods for large models. This paper investigates the latest technological advancements and the application of advanced methods in aspects such as task-adaptive fine-tuning,domain-adaptive fine-tuning,few-shot learning,knowledge distillation,multi-task learning,parameter-efficient fine-tuning,and dynamic fine-tuning.<|reference_end|>
@article{weng2024navigating,
    title={Navigating the Landscape of Large Language Models: A Comprehensive
  Review and Analysis of Paradigms and Fine-Tuning Strategies},
    author={Benjue Weng},
    journal={arXiv preprint arXiv:2404.09022},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.09022},
    primaryClass={cs.LG cs.AI cs.CL}
}