论文标题
集成梯度的最大熵基线
Maximum Entropy Baseline for Integrated Gradients
论文作者
论文摘要
综合梯度（IG）是可用的最流行的解释性方法之一，在选择基线的选择中仍然含糊不清，这可能会严重损害解释的信誉。这项研究提出了一个新的统一基线，即最大熵基线，这与Ig中定义的基准的“非信息”特性一致。此外，我们提出了一种改进的消融评估方法，其中包含了保持信息保守性的新基线。我们从信息的角度解释了Ig基准的线性变换不变性。最后，我们通过广泛的评估实验来评估不同解释性方法和不同的IG基准产生的解释的可靠性。
Integrated Gradients (IG), one of the most popular explainability methods available, still remains ambiguous in the selection of baseline, which may seriously impair the credibility of the explanations. This study proposes a new uniform baseline, i.e., the Maximum Entropy Baseline, which is consistent with the "uninformative" property of baselines defined in IG. In addition, we propose an improved ablating evaluation approach incorporating the new baseline, where the information conservativeness is maintained. We explain the linear transformation invariance of IG baselines from an information perspective. Finally, we assess the reliability of the explanations generated by different explainability methods and different IG baselines through extensive evaluation experiments.
