综述探讨基础模型在个性化联邦智能中的应用，汇总当前方法、挑战与未来方向。
arXiv:2505.06907v2 Announce Type: replace-cross Abstract: The rise of large language models (LLMs), such as ChatGPT, Gemini, and Grok, has reshaped th…
提出Ghosted Layers，无需训练即可恢复层剪枝后LLM的性能，通过激活对齐解决隐藏状态不匹配问题。
arXiv:2605.15491v1 Announce Type: cross Abstract: Layer pruning removes entire Transformer decoder blocks from large language models, but introduces a…
从被动回应到主动参与，最新研究教大模型何时该主动发言，突破传统对话边界。
arXiv:2508.18167v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in understanding and genera…
机器遗忘不仅能删除记忆，还能诱导模型产生可控的副作用行为与能力，颠覆了传统遗忘认知。
arXiv:2601.21702v3 Announce Type: replace Abstract: We consider Representation Misdirection (RM), a class of large language model (LLM) unlearning met…
多样信号集成监控比增加算力更能保障AI代理安全，这篇论文提出新思路。
arXiv:2605.15377v1 Announce Type: new Abstract: As AI systems are increasingly deployed in autonomous agentic settings at scale, it is important to en…
多轮对话中，长距离依赖与信息稀疏是老大难，这篇论文提出的Self-Recall Thinking框架，让模型在推理时主动召回历史关键轮次，无需外部模块，4.7% F1提升+14.7%延迟缩减，平衡了准确与效率，思路清奇。
arXiv:2605.15102v1 Announce Type: cross Abstract: Large language model (LLM) based multi-turn dialogue systems often struggle to track dependencies ac…
大模型在纵向电子病历推理中常因缺乏精细化统计导致幻觉，COTCAgent通过概率化思维链补全实现预防性咨询，为临床决策支持提供新范式。
arXiv:2605.15016v1 Announce Type: cross Abstract: As large language models empower healthcare, intelligent clinical decision support has developed rap…