探索如何通过微调大语言模型提升量子推理能力，来自arXiv的前沿研究。
arXiv:2606.21974v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit abilities beyond natural language modelling and text generation…
移动端原生微调框架，让LLM在手机等嵌入式设备上也能高效定制，突破云端限制
arXiv:2512.08211v2 Announce Type: replace Abstract: Large language models (LLMs) are moving from cloud-centric services toward on-device embedded AI, …
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…
为阿尔茨海默症辅助机器人量身定制，融合上下文学习与微调的LLM个性化方案
arXiv:2605.23941v1 Announce Type: new Abstract: Alzheimer's disease is a neurodegenerative disorder marked by progressive declines in memory and langu…
用语言代理实现大模型自主微调的创新框架，省去人工干预，让微调过程自动化
arXiv:2603.01712v2 Announce Type: replace-cross Abstract: Fine-tuning large language models for vertical domains remains labor-intensive, requiring pr…
从形式语言学习视角，剖析微调与上下文学习的根本差异，ACL 2026 重磅论文。
arXiv:2604.23267v2 Announce Type: replace-cross Abstract: Large language models (LLMs) operate in two fundamental learning modes - fine-tuning (FT) an…
揭秘LLM微调中对齐为何脆弱：从参数动态到输出分布的统一视角
arXiv:2605.18309v1 Announce Type: new Abstract: Although Large Language Models (LLMs) achieve strong alignment through supervised fine-tuning and rein…