这篇arXiv论文提出通过IoT数据预处理让边缘AI达到云级精度，值得技术研究者关注。
arXiv:2606.22496v1 Announce Type: cross Abstract: Large language models (LLMs) offer a natural-language interface for interpreting Internet of Things …
揭秘无训练AI图像检测器的脆弱性，系统评估分数方向、预处理与压缩的三重影响。
arXiv:2606.20488v1 Announce Type: new Abstract: Training-free detectors of AI-generated images promise generator-agnostic deployment without classifie…
利用结构化LLM流水线实现谈判预处理自动化，节省成本时间，让人工智能成为高效中介。
arXiv:2606.11379v1 Announce Type: new Abstract: Pre-mediation, the preparatory phase preceding direct human negotiation, plays a critical role in achi…
提出跨语言令牌套利新方法，用本地LLM预处理重写提示词，低成本优化代码代理上下文窗口。
arXiv:2606.03618v1 Announce Type: new Abstract: AI-assisted coding agents are bottlenecked by input-token cost. Two pathologies of raw human input dri…
训练大模型的数据质量怎么保证？这篇论文系统梳理了主流数据过滤方法，想做高效训练的不要错过。
arXiv:2605.29807v1 Announce Type: cross Abstract: Data quality is a critical factor in the effectiveness of machine learning models. Label errors, pre…
提出一种预处理正则化Wasserstein近端采样法，通过无噪声演化粒子高效逼近吉布斯分布，理论推导基于Cole-Hopf变换与各向异性热方程。
arXiv:2509.01685v2 Announce Type: replace-cross Abstract: We consider sampling from a Gibbs distribution by evolving finitely many particles. We propo…
利用几何建模进行尺度校正，提升高光谱图像解混性能的新预处理算法。
arXiv:2508.08431v3 Announce Type: replace-cross Abstract: Spectral variability significantly impacts the accuracy and convergence of hyperspectral unm…