diff --git a/reach/reach.py b/reach/reach.py
index 13d55a9..dca5100 100644
--- a/reach/reach.py
+++ b/reach/reach.py
@@ -702,8 +702,12 @@ def normalize(vectors: np.ndarray) -> np.ndarray:
         else:
             return vectors / norm[:, None]  # type: ignore
 
-    def vector_similarity(self, vector: np.ndarray, items: List[str]) -> np.ndarray:
+    def vector_similarity(
+        self, vector: np.ndarray, items: Union[str, List[str]]
+    ) -> np.ndarray:
         """Compute the similarity between a vector and a set of items."""
+        if isinstance(items, str):
+            items = [items]
         items_vec = np.stack([self.norm_vectors[self.items[item]] for item in items])
         return self._sim(vector, items_vec)
 
diff --git a/tests/test_similarity.py b/tests/test_similarity.py
index 6f6f2f9..04bae7f 100644
--- a/tests/test_similarity.py
+++ b/tests/test_similarity.py
@@ -166,3 +166,20 @@ def test_nearest_neighbor(self) -> None:
             ]
             nn2 = instance.threshold(word, threshold=threshold)[0]
             self.assertEqual(nn1, nn2)
+
+    def test_neighbor_similarity(self) -> None:
+        words, vectors = self.data()
+        instance = Reach(vectors, words)
+
+        result = instance.norm_vectors[0] @ instance.norm_vectors[1:].T
+        result2 = instance.vector_similarity(vectors[0], words[1:])
+
+        self.assertTrue(np.allclose(result, result2))
+
+        result = instance.norm_vectors[0] @ instance.norm_vectors[1].T
+        result2 = instance.vector_similarity(vectors[0], words[1])
+
+        self.assertEqual(result, result2)
+
+        result3 = instance.vector_similarity(vectors[0], [words[1]])
+        self.assertEqual(result2, result3)