diff --git a/xarray/core/dataset.py b/xarray/core/dataset.py
index 9f201557a60..ce5c6ee720e 100644
--- a/xarray/core/dataset.py
+++ b/xarray/core/dataset.py
@@ -4133,8 +4133,7 @@ def unstack(
                 # function requires.
                 # https://github.com/pydata/xarray/pull/4746#issuecomment-753282125
                 any(is_duck_dask_array(v.data) for v in self.variables.values())
-                # Sparse doesn't currently support advanced indexing
-                # https://github.com/pydata/sparse/issues/114
+                # sparse.COO doesn't currently support assignment
                 or any(
                     isinstance(v.data, sparse_array_type)
                     for v in self.variables.values()
diff --git a/xarray/core/variable.py b/xarray/core/variable.py
index bdbd1913547..48535f08958 100644
--- a/xarray/core/variable.py
+++ b/xarray/core/variable.py
@@ -1595,9 +1595,6 @@ def _unstack_once(
 
         if sparse:
             # unstacking a dense multitindexed array to a sparse array
-            # Use the sparse.COO constructor until sparse supports advanced indexing
-            # https://github.com/pydata/sparse/issues/114
-            # TODO: how do we allow different sparse array types
             from sparse import COO
 
             codes = zip(*index.codes)
@@ -1628,8 +1625,6 @@ def _unstack_once(
             # Indexer is a list of lists of locations. Each list is the locations
             # on the new dimension. This is robust to the data being sparse; in that
             # case the destinations will be NaN / zero.
-            # sparse doesn't support item assigment,
-            # https://github.com/pydata/sparse/issues/114
             data[(..., *indexer)] = reordered
 
         return self._replace(dims=new_dims, data=data)