diff --git a/cpp/src/reductions/reductions.cpp b/cpp/src/reductions/reductions.cpp
index 23171baaa45..cd1669d1d6b 100644
--- a/cpp/src/reductions/reductions.cpp
+++ b/cpp/src/reductions/reductions.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2019-2023, NVIDIA CORPORATION.
+ * Copyright (c) 2019-2024, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -177,15 +177,14 @@ std::unique_ptr<scalar> reduce(column_view const& col,
         std::move(*reduction::detail::make_empty_histogram_like(col.child(0))), true, stream, mr);
     }
 
-    if (output_dtype.id() == type_id::LIST) {
-      if (col.type() == output_dtype) { return make_empty_scalar_like(col, stream, mr); }
-      // Under some circumstance, the output type will become the List of input type,
-      // such as: collect_list or collect_set. So, we have to handcraft the default scalar.
+    if (agg.kind == aggregation::COLLECT_LIST || agg.kind == aggregation::COLLECT_SET) {
       auto scalar = make_list_scalar(empty_like(col)->view(), stream, mr);
       scalar->set_valid_async(false, stream);
       return scalar;
     }
-    if (output_dtype.id() == type_id::STRUCT) { return make_empty_scalar_like(col, stream, mr); }
+
+    // `make_default_constructed_scalar` does not support nested type.
+    if (cudf::is_nested(output_dtype)) { return make_empty_scalar_like(col, stream, mr); }
 
     auto result = make_default_constructed_scalar(output_dtype, stream, mr);
     if (agg.kind == aggregation::ANY || agg.kind == aggregation::ALL) {
diff --git a/cpp/tests/reductions/collect_ops_tests.cpp b/cpp/tests/reductions/collect_ops_tests.cpp
index 70aa7356ccb..65d0b3a54ad 100644
--- a/cpp/tests/reductions/collect_ops_tests.cpp
+++ b/cpp/tests/reductions/collect_ops_tests.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2022-2023, NVIDIA CORPORATION.
+ * Copyright (c) 2022-2024, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -367,3 +367,52 @@ TEST_F(CollectTest, CollectEmptys)
   ret = collect_set(all_nulls, cudf::make_collect_set_aggregation<cudf::reduce_aggregation>());
   CUDF_TEST_EXPECT_COLUMNS_EQUAL(int_col{}, dynamic_cast<cudf::list_scalar*>(ret.get())->view());
 }
+
+TEST_F(CollectTest, CollectAllNulls)
+{
+  using int_col = cudf::test::fixed_width_column_wrapper<int32_t>;
+  using namespace cudf::test::iterators;
+
+  auto const input    = int_col{{0, 0, 0, 0, 0, 0}, all_nulls()};
+  auto const expected = int_col{};
+
+  {
+    auto const agg =
+      cudf::make_collect_list_aggregation<cudf::reduce_aggregation>(cudf::null_policy::EXCLUDE);
+    auto const result = cudf::reduce(input, *agg, cudf::data_type{cudf::type_id::LIST});
+    CUDF_TEST_EXPECT_COLUMNS_EQUAL(expected,
+                                   dynamic_cast<cudf::list_scalar*>(result.get())->view());
+  }
+  {
+    auto const agg = cudf::make_collect_set_aggregation<cudf::reduce_aggregation>(
+      cudf::null_policy::EXCLUDE, cudf::null_equality::UNEQUAL, cudf::nan_equality::ALL_EQUAL);
+    auto const result = cudf::reduce(input, *agg, cudf::data_type{cudf::type_id::LIST});
+    CUDF_TEST_EXPECT_COLUMNS_EQUAL(expected,
+                                   dynamic_cast<cudf::list_scalar*>(result.get())->view());
+  }
+}
+
+TEST_F(CollectTest, CollectAllNullsWithLists)
+{
+  using LCW = cudf::test::lists_column_wrapper<int32_t>;
+  using namespace cudf::test::iterators;
+
+  // list<list<int>>
+  auto const input    = LCW{{LCW{LCW{1, 2, 3}, LCW{4, 5, 6}}, LCW{{1, 2, 3}}}, all_nulls()};
+  auto const expected = cudf::empty_like(input);
+
+  {
+    auto const agg =
+      cudf::make_collect_list_aggregation<cudf::reduce_aggregation>(cudf::null_policy::EXCLUDE);
+    auto const result = cudf::reduce(input, *agg, cudf::data_type{cudf::type_id::LIST});
+    CUDF_TEST_EXPECT_COLUMNS_EQUAL(expected->view(),
+                                   dynamic_cast<cudf::list_scalar*>(result.get())->view());
+  }
+  {
+    auto const agg = cudf::make_collect_set_aggregation<cudf::reduce_aggregation>(
+      cudf::null_policy::EXCLUDE, cudf::null_equality::UNEQUAL, cudf::nan_equality::ALL_EQUAL);
+    auto const result = cudf::reduce(input, *agg, cudf::data_type{cudf::type_id::LIST});
+    CUDF_TEST_EXPECT_COLUMNS_EQUAL(expected->view(),
+                                   dynamic_cast<cudf::list_scalar*>(result.get())->view());
+  }
+}