plot.model_performance_explainer outliers' labels depend on the order of model input about dalex HOT 2 OPEN

library("DALEX")
#> Welcome to DALEX (version: 2.4.3).
#> Find examples and detailed introduction at: http://ema.drwhy.ai/
library("randomForest")
#> randomForest 4.7-1.1
#> Type rfNews() to see new features/changes/bug fixes.

model_apart_lm <- archivist::aread("pbiecek/models/55f19")
explain_apart_lm <- DALEX::explain(model = model_apart_lm, 
                                   data    = apartments_test[,-1], 
                                   y       = apartments_test$m2.price, 
                                   label   = "Linear Regression")
#> Preparation of a new explainer is initiated
#>   -> model label       :  Linear Regression 
#>   -> data              :  9000  rows  5  cols 
#>   -> target variable   :  9000  values 
#>   -> predict function  :  yhat.lm  will be used (  default  )
#>   -> predicted values  :  No value for predict function target column. (  default  )
#>   -> model_info        :  package stats , ver. 4.2.3 , task regression (  default  ) 
#>   -> predicted values  :  numerical, min =  1792.597 , mean =  3506.836 , max =  6241.447  
#>   -> residual function :  difference between y and yhat (  default  )
#>   -> residuals         :  numerical, min =  -257.2555 , mean =  4.687686 , max =  472.356  
#>   A new explainer has been created!

model_apart_rf <- archivist::aread("pbiecek/models/fe7a5")
explain_apart_rf <- DALEX::explain(model = model_apart_rf, 
                                   data    = apartments_test[,-1], 
                                   y       = apartments_test$m2.price, 
                                   label   = "Random Forest")
#> Preparation of a new explainer is initiated
#>   -> model label       :  Random Forest 
#>   -> data              :  9000  rows  5  cols 
#>   -> target variable   :  9000  values 
#>   -> predict function  :  yhat.randomForest  will be used (  default  )
#>   -> predicted values  :  No value for predict function target column. (  default  )
#>   -> model_info        :  package randomForest , ver. 4.7.1.1 , task regression (  default  ) 
#>   -> predicted values  :  numerical, min =  1985.837 , mean =  3506.107 , max =  5788.052  
#>   -> residual function :  difference between y and yhat (  default  )
#>   -> residuals         :  numerical, min =  -762.3422 , mean =  5.416971 , max =  1318.093  
#>   A new explainer has been created!

mr_lm <- DALEX::model_performance(explain_apart_lm)
mr_rf <- DALEX::model_performance(explain_apart_rf)

# Works good
plot(mr_rf, mr_lm, 
     geom = "boxplot",
     show_outliers = 1)

# Doesn't assing the outliners correctly
plot(mr_lm, mr_rf, 
     geom = "boxplot",
     show_outliers = 1)