本文评估了 RemOve-And-Retrain (ROAR) 协议的可靠性，发现其性能指标不受决策函数信息影响，并提出了 DoRaR 特征归属方法，以提高黑盒模型的透明度。同时，研究提出了 ART 训练方法，显著增强了解释的鲁棒性，并在多个数据集上取得最佳性能。此外，介绍了 eXplanation-based Counterfactual Retraining (XCR) 方法，旨在优化黑盒模型并解决解释性人工智能的问题。

tonight I am going to see cursive. it should be fun. I really like that band. but what I like more is this. It is very funny. ;) ;)So we are at war. but at what cost? I imagine it will cost a lot...