public Builder mergeXraiAttribution(com.google.cloud.vertexai.api.XraiAttribution value) {
      if (xraiAttributionBuilder_ == null) {
        if (methodCase_ == 3
            && method_ != com.google.cloud.vertexai.api.XraiAttribution.getDefaultInstance()) {
          method_ =
              com.google.cloud.vertexai.api.XraiAttribution.newBuilder(
                      (com.google.cloud.vertexai.api.XraiAttribution) method_)
                  .mergeFrom(value)
                  .buildPartial();
        } else {
          method_ = value;
        }
        onChanged();
      } else {
        if (methodCase_ == 3) {
          xraiAttributionBuilder_.mergeFrom(value);
        } else {
          xraiAttributionBuilder_.setMessage(value);
        }
      }
      methodCase_ = 3;
      return this;
    }
<pre>
An attribution method that redistributes Integrated Gradients
attribution to segmented regions, taking advantage of the model's fully
differentiable structure. Refer to this paper for
more details: https://arxiv.org/abs/1906.02825

XRAI currently performs better on natural images, like a picture of a
house or an animal. If the images are taken in artificial environments,
like a lab or manufacturing line, or from diagnostic equipment, like
x-rays or quality-control cameras, use Integrated Gradients instead.
</pre>

<code>.google.cloud.vertexai.v1.XraiAttribution xrai_attribution = 3;</code>
java-vertexai/proto-google-cloud-vertexai-v1/src/main/java/com/google/cloud/vertexai/api/ExplanationParameters.java