diff --git a/python/python/lancedb/table.py b/python/python/lancedb/table.py
index 28ee37fbf..f4d70077c 100644
--- a/python/python/lancedb/table.py
+++ b/python/python/lancedb/table.py
@@ -651,6 +651,16 @@ def _append_vector_columns(
                     col_data = func.compute_source_embeddings_with_retry(
                         batch[conf.source_column]
                     )
+                    # Replace vectors with wrong length (including empty lists
+                    # returned for inputs like empty strings) with None so that
+                    # _handle_bad_vectors can process them according to the
+                    # on_bad_vectors policy instead of crashing when PyArrow
+                    # tries to cast them into a fixed-size list array.
+                    expected_ndims = conf.function.ndims()
+                    col_data = [
+                        v if v is not None and len(v) == expected_ndims else None
+                        for v in col_data
+                    ]
                     if no_vector_column:
                         batch = batch.append_column(
                             schema.field(vector_column),
@@ -4020,7 +4030,16 @@ def _handle_bad_vector_column(
         dim = _infer_vector_dim(vec_arr)
         if dim is None:
             return data
-    has_wrong_dim = pc.not_equal(pc.list_value_length(vec_arr), dim)
+
+    is_null = pc.is_null(vec_arr)
+    # pc.list_value_length returns null for null list entries, so
+    # pc.not_equal(null, dim) also returns null. Use or_kleene so that
+    # True OR null = True (Kleene three-valued logic), ensuring null vectors
+    # are counted as wrong-dim.
+    has_wrong_dim = pc.or_kleene(
+        is_null,
+        pc.not_equal(pc.list_value_length(vec_arr), dim),
+    )
 
     has_bad_vectors = pc.any(has_nan).as_py() or pc.any(has_wrong_dim).as_py()
 
diff --git a/python/python/tests/test_embeddings.py b/python/python/tests/test_embeddings.py
index 43f7b44ac..c0cdf1c0d 100644
--- a/python/python/tests/test_embeddings.py
+++ b/python/python/tests/test_embeddings.py
@@ -242,6 +242,49 @@ def test_embedding_with_bad_results(tmp_path):
     assert tbl["vector"].null_count == 1
 
 
+def test_embedding_with_empty_output_vectors(tmp_path):
+    """Regression test for issue #1672.
+
+    When an embedding function returns an empty list (e.g. for empty-string
+    inputs), _append_vector_columns used to crash because PyArrow cannot cast
+    [] into a fixed-size list element.  The fix replaces wrong-length vectors
+    with None before building the Arrow array so that _handle_bad_vectors can
+    process them normally.
+    """
+
+    @register("empty-vec-embedding")
+    class EmptyVecEmbeddingFunction(TextEmbeddingFunction):
+        def ndims(self):
+            return 128
+
+        def generate_embeddings(self, texts: Union[List[str], np.ndarray]) -> list:
+            # Simulate a model that returns an empty list for blank inputs
+            return [
+                [] if text.strip() == "" else np.random.randn(self.ndims()).tolist()
+                for text in texts
+            ]
+
+    db = lancedb.connect(tmp_path)
+    registry = EmbeddingFunctionRegistry.get_instance()
+    model = registry.get("empty-vec-embedding").create()
+
+    class Schema(LanceModel):
+        text: str = model.SourceField()
+        vector: Vector(model.ndims()) = model.VectorField()
+
+    table = db.create_table("test_empty_vec", schema=Schema, mode="overwrite")
+
+    # Should not crash; the row with the empty string should be dropped
+    table.add(
+        [{"text": "hello world"}, {"text": ""}, {"text": "foo"}],
+        on_bad_vectors="drop",
+    )
+
+    assert len(table) == 2
+    texts = table.to_arrow()["text"].to_pylist()
+    assert "" not in texts
+
+
 def test_with_existing_vectors(tmp_path):
     @register("mock-embedding")
     class MockEmbeddingFunction(TextEmbeddingFunction):