本期“TAI快报”介绍了四篇AI前沿论文的关键内容： 《Inside-Out: Hidden Factual Knowledge in LLMs》《Inside-Out: LLMs中的隐藏事实知识》揭示大型语言模型内部藏有超乎输出的“隐藏事实知识”，通过内外知识对比，发现生成能力是瓶颈，未来优化可提升问答准确性。 《Value Profiles for Encoding Human Variation》《编码人类变异的价值配置文件》提出“价值观画像”用自然语言捕捉人类评分差异，优于传统统计方法，可用于个性化推荐和行为研究。 《RAGO: Systematic Performance Optimization for Retrieval-Augmented Generation Serving》《RAGO：用于检索增强生成的系统性能优化》推出RAGO框架优化检索增强生成系统，显著提升查询效率和响应速度，适用于智能搜索等场景。 《Robustness of Nonlinear Representation Learning》《非线性表示学习鲁棒性》证明非线性表示学习在数据不完美时仍具鲁棒性，为处理现实世界的复杂数据奠定理论基础。完整推介：https://mp.weixin.qq.com/s/WKgf4nOZRtQSPrIY6EtSLg
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