We present AIREPAIR, a platform for repairing neural networks. It features the integration of existing network repair tools. Based on AIREPAIR, one can run different repair methods on the same model, thus enabling the fair comparison of different repair techniques. We evaluate AIREPAIR with three state-of-the-art repair tools on popular deep-learning datasets and models. Our evaluation confirms the utility of AIREPAIR, by comparing and analyzing the results from different repair techniques. A demonstration is available at https://youtu.be/UkKw5neeWhw.
翻译:我们提出了AIREPAIR,一个神经网络修复平台。它集成了现有的网络修复工具。在AIREPAIR的基础上,可以在同一模型上运行不同的修复方法,从而使得不同的修复技术可以进行公平比较。我们使用三个最先进的修复工具在受欢迎的深度学习数据集和模型上进行了AIREPAIR的评估。我们的评估确认了AIREPAIR的实用性,通过比较和分析来自不同修复技术的结果。演示视频可在 https://youtu.be/UkKw5neeWhw 上观看。