提出分布优化数据合成方法，系统拓展LLM知识边界，有效减少幻觉。
arXiv:2606.23271v1 Announce Type: new Abstract: Knowledge injection via synthetic data is crucial for enhancing Large Language Models (LLMs). However,…
为LLM生成电力系统代码引入知识边界探测与需求引导干预机制，提升准确性与可靠性
arXiv:2605.31478v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to automate power-system analysis, but many utili…
新基准BeQu用万级实体检验LLM知识边界，揭示推理努力与模型规模对知识判断的影响。
arXiv:2605.26937v1 Announce Type: cross Abstract: Parametric knowledge in large language models (LLMs) is a cornerstone of their success, yet remains …
揭秘大模型“未来知识”作弊：时间批判让AI学会说“不知道”
arXiv:2605.14636v1 Announce Type: new Abstract: Large language models (LLMs) often fail to reason under temporal cutoffs: when prompted to answer from…