diff --git a/docs/test/test_documentation_examples.py b/docs/test/test_documentation_examples.py
index 3cf7ac3b30..3931bdfd15 100644
--- a/docs/test/test_documentation_examples.py
+++ b/docs/test/test_documentation_examples.py
@@ -6,6 +6,11 @@
 import sys
 import unittest
 
+import torch
+
+from onnxscript import evaluator
+from onnxscript.function_libs.torch_lib import ops
+
 
 class TestDocumentationExample(unittest.TestCase):
     def do_test_folder(self, folder):
@@ -22,8 +27,7 @@ def do_test_folder(self, folder):
                 with subprocess.Popen(
                     cmds, stdout=subprocess.PIPE, stderr=subprocess.PIPE
                 ) as p:
-                    res = p.communicate()
-                    _, err = res
+                    _, err = p.communicate()
                     st = err.decode("ascii", errors="ignore")
                     if len(st) > 0 and "Traceback" in st:
                         raise RuntimeError(  # pylint: disable=W0707
@@ -54,5 +58,18 @@ def test(*relpath):
         test("..", "..", "docs", "tutorial", "rewriter", "examples")
 
 
+def test_unbind_matches_torch():
+    x_torch = torch.randn(3, 4)
+    y_torch = torch.unbind(x_torch, dim=1)
+
+    x_np = x_torch.detach().cpu().numpy()
+    eager = evaluator.default()
+    y_onnx = eager.eval_function(ops.core.aten_unbind, (x_np,), {"dim": 1})
+
+    assert len(y_torch) == len(y_onnx)
+    for a, b in zip(y_torch, y_onnx):
+        assert a.shape == tuple(b.shape), f"Shape mismatch: {a.shape} vs {b.shape}"
+
+
 if __name__ == "__main__":
     unittest.main(verbosity=2)
diff --git a/onnxscript/function_libs/torch_lib/ops/core.py b/onnxscript/function_libs/torch_lib/ops/core.py
index ab992e0580..1b68b80b38 100644
--- a/onnxscript/function_libs/torch_lib/ops/core.py
+++ b/onnxscript/function_libs/torch_lib/ops/core.py
@@ -8618,10 +8618,13 @@ def aten_type_as(self: TTensor, other: TTensor2) -> TTensor2:
 
 @torch_op("aten::unbind.int")
 def aten_unbind(self: TTensor, dim: int = 0) -> Sequence[TTensor]:
-    """unbind.int(Tensor(a -> *) self, int dim=0) -> Tensor(a)[]"""
+    """unbind(Tensor self, int dim=0) -> Tensor[]
 
-    split_sizes = op.Constant(value_int=1)
-    return op.SplitToSequence(self, split_sizes, axis=dim, keepdims=False)
+    Splits a tensor into multiple tensors along the given dimension without keeping the dimension.
+    Matches the behavior of torch.unbind.
+    """
+    split_size = op.Constant(value_int=1)
+    return op.SplitToSequence(self, split_size, axis=dim, keepdims=False)
 
 
 @torch_op("aten::unflatten.int", trace_only=True)