diff --git a/R-package/R/xgb.Booster.R b/R-package/R/xgb.Booster.R
index 6ffaa299b500..011c73ab5892 100644
--- a/R-package/R/xgb.Booster.R
+++ b/R-package/R/xgb.Booster.R
@@ -1055,6 +1055,10 @@ xgb.best_iteration <- function(bst) {
   return(out)
 }
 
+xgb.has_categ_features <- function(bst) {
+  return("c" %in% xgb.feature_types(bst))
+}
+
 #' Extract coefficients from linear booster
 #'
 #' @description
diff --git a/R-package/R/xgb.model.dt.tree.R b/R-package/R/xgb.model.dt.tree.R
index 789737d4c701..cb7a51a1e555 100644
--- a/R-package/R/xgb.model.dt.tree.R
+++ b/R-package/R/xgb.model.dt.tree.R
@@ -2,10 +2,12 @@
 #'
 #' Parse a boosted tree model text dump into a `data.table` structure.
 #'
+#' Note that this function does not work with models that were fitted to
+#' categorical data, and is only applicable to tree-based boosters (not `gblinear`).
 #' @param model Object of class `xgb.Booster`. If it contains feature names (they can
 #'   be set through [setinfo()]), they will be used in the output from this function.
-#' @param text Character vector previously generated by the function [xgb.dump()]
-#'   (called with parameter `with_stats = TRUE`). `text` takes precedence over `model`.
+#'
+#'   If the model contains categorical features, an error will be thrown.
 #' @param trees An integer vector of (base-1) tree indices that should be used. The default
 #'   (`NULL`) uses all trees. Useful, e.g., in multiclass classification to get only
 #'   the trees of one class.
@@ -64,14 +66,15 @@
 #' ]
 #'
 #' @export
-xgb.model.dt.tree <- function(model = NULL, text = NULL,
-                              trees = NULL, use_int_id = FALSE, ...) {
+xgb.model.dt.tree <- function(model, trees = NULL, use_int_id = FALSE, ...) {
   check.deprecation(deprecated_dttree_params, match.call(), ...)
 
-  if (!inherits(model, "xgb.Booster") && !is.character(text)) {
-    stop("Either 'model' must be an object of class xgb.Booster\n",
-         "  or 'text' must be a character vector with the result of xgb.dump\n",
-         "  (or NULL if 'model' was provided).")
+  if (!inherits(model, "xgb.Booster")) {
+    stop("Either 'model' must be an object of class xgb.Booster")
+  }
+
+  if (xgb.has_categ_features(model)) {
+    stop("Cannot produce tables for models having categorical features.")
   }
 
   if (!is.null(trees)) {
@@ -89,11 +92,7 @@ xgb.model.dt.tree <- function(model = NULL, text = NULL,
     feature_names <- xgb.feature_names(model)
   }
 
-  from_text <- TRUE
-  if (is.null(text)) {
-    text <- xgb.dump(model = model, with_stats = TRUE)
-    from_text <- FALSE
-  }
+  text <- xgb.dump(model = model, with_stats = TRUE)
 
   if (length(text) < 2 || !any(grepl('leaf=(-?\\d+)', text))) {
     stop("Non-tree model detected! This function can only be used with tree models.")
@@ -130,15 +129,7 @@ xgb.model.dt.tree <- function(model = NULL, text = NULL,
     branch_rx <- branch_rx_w_names
     text_has_feature_names <- TRUE
   } else {
-    # Note: when passing a text dump, it might or might not have feature names,
-    # but that aspect is unknown from just the text attributes
     branch_rx <- branch_rx_nonames
-    if (from_text) {
-      if (sum(grepl(branch_rx_w_names, text)) > sum(grepl(branch_rx_nonames, text))) {
-        branch_rx <- branch_rx_w_names
-        text_has_feature_names <- TRUE
-      }
-    }
   }
   branch_cols <- c("Feature", "Split", "Yes", "No", "Missing", "Gain", "Cover")
   td[
diff --git a/R-package/R/xgb.plot.multi.trees.R b/R-package/R/xgb.plot.multi.trees.R
index 1c57dd84babd..e67a4ec7eab9 100644
--- a/R-package/R/xgb.plot.multi.trees.R
+++ b/R-package/R/xgb.plot.multi.trees.R
@@ -2,6 +2,8 @@
 #'
 #' Visualization of the ensemble of trees as a single collective unit.
 #'
+#' Note that this function does not work with models that were fitted to
+#' categorical data.
 #' @details
 #' This function tries to capture the complexity of a gradient boosted tree model
 #' in a cohesive way by compressing an ensemble of trees into a single tree-graph representation.
@@ -64,10 +66,16 @@
 #' @export
 xgb.plot.multi.trees <- function(model, features_keep = 5, plot_width = NULL, plot_height = NULL,
                                  render = TRUE, ...) {
+  check.deprecation(deprecated_multitrees_params, match.call(), ...)
   if (!requireNamespace("DiagrammeR", quietly = TRUE)) {
     stop("DiagrammeR is required for xgb.plot.multi.trees")
   }
-  check.deprecation(deprecated_multitrees_params, match.call(), ...)
+  if (xgb.has_categ_features(model)) {
+    stop(
+      "Cannot use 'xgb.plot.multi.trees' for models with categorical features.",
+      " Try 'xgb.plot.tree' instead."
+    )
+  }
   tree.matrix <- xgb.model.dt.tree(model = model)
 
   # first number of the path represents the tree, then the following numbers are related to the path to follow
diff --git a/R-package/man/xgb.model.dt.tree.Rd b/R-package/man/xgb.model.dt.tree.Rd
index 424552e490cd..8495cb2ac77a 100644
--- a/R-package/man/xgb.model.dt.tree.Rd
+++ b/R-package/man/xgb.model.dt.tree.Rd
@@ -4,20 +4,13 @@
 \alias{xgb.model.dt.tree}
 \title{Parse model text dump}
 \usage{
-xgb.model.dt.tree(
-  model = NULL,
-  text = NULL,
-  trees = NULL,
-  use_int_id = FALSE,
-  ...
-)
+xgb.model.dt.tree(model, trees = NULL, use_int_id = FALSE, ...)
 }
 \arguments{
 \item{model}{Object of class \code{xgb.Booster}. If it contains feature names (they can
-be set through \code{\link[=setinfo]{setinfo()}}), they will be used in the output from this function.}
+be set through \code{\link[=setinfo]{setinfo()}}), they will be used in the output from this function.
 
-\item{text}{Character vector previously generated by the function \code{\link[=xgb.dump]{xgb.dump()}}
-(called with parameter \code{with_stats = TRUE}). \code{text} takes precedence over \code{model}.}
+If the model contains categorical features, an error will be thrown.}
 
 \item{trees}{An integer vector of (base-1) tree indices that should be used. The default
 (\code{NULL}) uses all trees. Useful, e.g., in multiclass classification to get only
@@ -59,6 +52,10 @@ the corresponding trees in the "Node" column.
 \description{
 Parse a boosted tree model text dump into a \code{data.table} structure.
 }
+\details{
+Note that this function does not work with models that were fitted to
+categorical data, and is only applicable to tree-based boosters (not \code{gblinear}).
+}
 \examples{
 # Basic use:
 
diff --git a/R-package/man/xgb.plot.multi.trees.Rd b/R-package/man/xgb.plot.multi.trees.Rd
index 989096e60e42..a6be36b97d53 100644
--- a/R-package/man/xgb.plot.multi.trees.Rd
+++ b/R-package/man/xgb.plot.multi.trees.Rd
@@ -43,6 +43,9 @@ line.
 Visualization of the ensemble of trees as a single collective unit.
 }
 \details{
+Note that this function does not work with models that were fitted to
+categorical data.
+
 This function tries to capture the complexity of a gradient boosted tree model
 in a cohesive way by compressing an ensemble of trees into a single tree-graph representation.
 The goal is to improve the interpretability of a model generally seen as black box.
diff --git a/R-package/tests/testthat/test_helpers.R b/R-package/tests/testthat/test_helpers.R
index 26a555ea55e3..1e1054e73617 100644
--- a/R-package/tests/testthat/test_helpers.R
+++ b/R-package/tests/testthat/test_helpers.R
@@ -356,9 +356,8 @@ test_that("xgb.importance works with and without feature names", {
   importance <- xgb.importance(feature_names = feature.names, model = bst.Tree, trees = trees)
 
   importance_from_dump <- function() {
-    model_text_dump <- xgb.dump(model = bst.Tree, with_stats = TRUE)
     imp <- xgb.model.dt.tree(
-      text = model_text_dump,
+      model = bst.Tree,
       trees = trees
     )[
       Feature != "Leaf", .(