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AIREPAIR，一个用于修复神经网络的平台。该平台集成了现有网络修复工具。基于AIREPAIR，用户可在同一模型上运行不同的修复方法，从而实现对不同修复技术的公平比较。我们使用三种最先进的修复工具，在主流深度学习数据集和模型上对AIREPAIR进行了评估。通过比较和分析不同修复技术的结果，我们的评估验证了AIREPAIR的实用性。演示视频请访问 https://youtu.be/UkKw5neeWhw。