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：我们介绍AIREPAIR,这是一个修复神经网络的平台,其特点是整合现有的网络修复工具;根据AIREPAIR, 一个人可以在同一模型上使用不同的修复方法,从而能够对不同的修复技术进行公平的比较;我们用三种最先进的关于广受欢迎的深造数据集和模型的修复工具对AIREPAIR进行评估;我们的评估通过比较和分析不同修复技术的结果,证实了AIREPAIR的效用;在https://youtu.be/UkKw5neewwww上可以提供示范。