边缘设备微调LLM的突破：LoRA峰值内存优化技术详解
arXiv:2606.19528v1 Announce Type: cross Abstract: Fine-tuning of Large Language Models (LLMs) using Low-Rank Adaptation (LoRA) on an end-user's data o…
重新审视低秩适应（LoRA）在私有LLM微调中的应用，探讨差分隐私与效率的平衡。
arXiv:2510.01137v3 Announce Type: replace Abstract: Privacy is a central concern when fine-tuning large language models (LLMs) on sensitive data, and …
NaRA提出噪声感知LoRA，显著提升扩散大语言模型参数高效微调效果
arXiv:2605.29716v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have emerged as a promising non-autoregressive generative para…
混合全微调与低秩适应的新方法，专为后训练场景优化，效率与性能兼得
arXiv:2605.18822v1 Announce Type: new Abstract: Post-training has become essential for adapting large language models (LLMs) to complex downstream beh…
策略性过参数化提升低秩适应泛化能力，为参数高效微调提供新理论。
arXiv:2605.16470v1 Announce Type: new Abstract: Adapting large language models (LLMs) to downstream tasks via full fine-tuning is increasingly impract…