  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.
