diff --git a/cpp/src/neighbors/detail/nn_descent.cuh b/cpp/src/neighbors/detail/nn_descent.cuh
index 310d4e7a6..dffc94f06 100644
--- a/cpp/src/neighbors/detail/nn_descent.cuh
+++ b/cpp/src/neighbors/detail/nn_descent.cuh
@@ -1047,24 +1047,32 @@ void GnndGraph<Index_t>::init_random_graph()
   for (size_t seg_idx = 0; seg_idx < static_cast<size_t>(num_segments); seg_idx++) {
     // random sequence (range: 0~nrow)
     // segment_x stores neighbors which id % num_segments == x
-    std::vector<Index_t> rand_seq(nrow / num_segments);
+    std::vector<Index_t> rand_seq((nrow + num_segments - 1) / num_segments);
     std::iota(rand_seq.begin(), rand_seq.end(), 0);
     auto gen = std::default_random_engine{seg_idx};
     std::shuffle(rand_seq.begin(), rand_seq.end(), gen);
 
 #pragma omp parallel for
     for (size_t i = 0; i < nrow; i++) {
-      size_t base_idx      = i * node_degree + seg_idx * segment_size;
-      auto h_neighbor_list = h_graph + base_idx;
-      auto h_dist_list     = h_dists.data_handle() + base_idx;
+      size_t base_idx         = i * node_degree + seg_idx * segment_size;
+      auto h_neighbor_list    = h_graph + base_idx;
+      auto h_dist_list        = h_dists.data_handle() + base_idx;
+      size_t idx              = base_idx;
+      size_t self_in_this_seg = 0;
       for (size_t j = 0; j < static_cast<size_t>(segment_size); j++) {
-        size_t idx = base_idx + j;
         Index_t id = rand_seq[idx % rand_seq.size()] * num_segments + seg_idx;
         if ((size_t)id == i) {
-          id = rand_seq[(idx + segment_size) % rand_seq.size()] * num_segments + seg_idx;
+          idx++;
+          id               = rand_seq[idx % rand_seq.size()] * num_segments + seg_idx;
+          self_in_this_seg = 1;
         }
-        h_neighbor_list[j].id_with_flag() = id;
-        h_dist_list[j]                    = std::numeric_limits<DistData_t>::max();
+
+        h_neighbor_list[j].id_with_flag() =
+          j < (rand_seq.size() - self_in_this_seg) && size_t(id) < nrow
+            ? id
+            : std::numeric_limits<Index_t>::max();
+        h_dist_list[j] = std::numeric_limits<DistData_t>::max();
+        idx++;
       }
     }
   }
diff --git a/cpp/tests/neighbors/ann_cagra.cuh b/cpp/tests/neighbors/ann_cagra.cuh
index 1e695f9a8..e9408264e 100644
--- a/cpp/tests/neighbors/ann_cagra.cuh
+++ b/cpp/tests/neighbors/ann_cagra.cuh
@@ -952,6 +952,12 @@ class AnnCagraIndexMergeTest : public ::testing::TestWithParam<AnnCagraInputs> {
         (ps.k * ps.dim * 8 / 5 /*(=magic number)*/ < ps.n_rows))
       GTEST_SKIP();
 
+    // Avoid splitting datasets with a size of 0
+    if (ps.n_rows <= 3) GTEST_SKIP();
+
+    // IVF_PQ requires the `n_rows >= n_lists`.
+    if (ps.n_rows < 8 && ps.build_algo == graph_build_algo::IVF_PQ) GTEST_SKIP();
+
     size_t queries_size = ps.n_queries * ps.k;
     std::vector<IdxT> indices_Cagra(queries_size);
     std::vector<IdxT> indices_naive(queries_size);
@@ -1161,6 +1167,24 @@ inline std::vector<AnnCagraInputs> generate_inputs()
     {0.995});
   inputs.insert(inputs.end(), inputs2.begin(), inputs2.end());
 
+  // Corner cases for small datasets
+  inputs2 = raft::util::itertools::product<AnnCagraInputs>(
+    {2},
+    {3, 5, 31, 32, 64, 101},
+    {1, 10},
+    {2},  // k
+    {graph_build_algo::IVF_PQ, graph_build_algo::NN_DESCENT},
+    {search_algo::SINGLE_CTA, search_algo::MULTI_CTA, search_algo::MULTI_KERNEL},
+    {0},  // query size
+    {0},
+    {256},
+    {1},
+    {cuvs::distance::DistanceType::L2Expanded},
+    {false},
+    {true},
+    {0.995});
+  inputs.insert(inputs.end(), inputs2.begin(), inputs2.end());
+
   // Varying dim and build algo.
   inputs2 = raft::util::itertools::product<AnnCagraInputs>(
     {100},