融合LoRA与Soft Prompting优势，用强化学习机制微调多模态大模型的新方案ART。
arXiv:2606.11854v1 Announce Type: cross Abstract: There are two main Parameter-Efficient Fine-Tuning (PEFT) techniques for Large Language Models (LLMs…
多任务微调新方法，用连续提示优化实现参数高效的大模型适配，减少数据需求。
arXiv:2605.14055v1 Announce Type: cross Abstract: Parameter-Efficient Fine-Tuning (PEFT) is widely used for adapting Large Language Models (LLMs) for …
新微调方法PreFT仅优化预填充阶段，解决大模型个性化服务时PEFT导致的吞吐量瓶颈，理论与实证兼备。
arXiv:2605.14217v1 Announce Type: cross Abstract: Large language models can now be personalised efficiently at scale using parameter efficient finetun…