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新框架对神经网络中的信任进行建模和传播

一个名为 PaTAS 的新框架已被开发出来,用于使用主观逻辑在神经网络中建模和传播信任。该系统与标准的神经网络计算并行运行,采用信任节点(Trust Nodes)和信任函数(Trust Functions)来评估和传递与输入、参数和激活相关的信任水平。PaTAS 包括在训练期间优化参数可靠性的机制,以及在推理期间计算实例特定信任值的机制,证明了其提供可解释的信任估计的能力,这些估计可以补充准确性指标并突出数据中的可靠性问题。 AI

影响 引入了一种量化和推理人工智能系统中信任度的新方法,这对于安全关键型应用至关重要。

排序理由 这是一篇介绍人工智能安全新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新框架对神经网络中的信任进行建模和传播

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这是一篇介绍人工智能安全新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Koffi Ismael Ouattara, Ioannis Krontiris, Theo Dimitrakos, Dennis Eisermann, Houda Labiod, Frank Kargl ·

    PaTAS:一种使用主观逻辑在神经网络中进行信任传播的框架

    arXiv:2511.20586v4 Announce Type: replace Abstract: Trustworthiness has become a key requirement for the deployment of artificial intelligence systems in safety-critical applications. Conventional evaluation metrics, such as accuracy and precision, fail to appropriately capture u…