Result from the plot function is an ggplot2 object, thus you can use xlim() ylim() or other function to zoom in some part of the plot.

But I see your point, that for model_performance it would be nice to have annotations for top k residuals. Will add to TODO

I've added a show_outliers parameter to plot.model_performance(), now you can plot names of points with largest residuals.
See an example here: https://pbiecek.github.io/DALEX/reference/plot.model_performance_explainer.html

Would it be more meaningful to have the names of points with largest residuals to correspond to the observed data row index? This will make it easier for users to identify which observation has the worst prediction.

Using https://pbiecek.github.io/DALEX/reference/plot.model_performance_explainer.html as an example. We gave the largest residual in the glm model a name of 100,110. This is very confusing to the users since the validation dataset only have 14,999 row

Would it be possible to add an index column in the model_performace() output so the boxplot can use that index number when identifying largest residual instead of the number now?

Makes sense, will add option to select if rownames of row indexes should be presented