diff --git a/onnxscript/function_libs/torch_aten/ops/core.py b/onnxscript/function_libs/torch_aten/ops/core.py
index 67d0106684..b49e5fe40b 100644
--- a/onnxscript/function_libs/torch_aten/ops/core.py
+++ b/onnxscript/function_libs/torch_aten/ops/core.py
@@ -769,6 +769,12 @@ def aten_bitwise_not(self: TInt) -> TInt:
     return op.BitwiseNot(self)
 
 
+@torch_op("aten::bitwise_not", overload=True)
+def aten_bitwise_not_bool(self: BOOL) -> BOOL:
+    # bitwise_not(Tensor self) -> Tensor
+    return op.Not(self)
+
+
 @torch_op("aten::bitwise_or")
 def aten_bitwise_or(self: TInt, other: TInt) -> TInt:
     # bitwise_or.Tensor(Tensor self, Tensor other) -> Tensor
@@ -3146,9 +3152,10 @@ def aten_margin_ranking_loss(
 @torch_op("aten::masked_fill")
 def aten_masked_fill(self: TTensor, mask: BOOL, value: TTensor) -> TTensor:
     # masked_fill.Tensor(Tensor self, Tensor mask, Tensor value) -> Tensor
-    mask_cast = op.Cast(mask, to=BOOL.dtype)
+    # NOTE: Do not attempt to cast `mask` to BOOL because mask should not take any other types.
+    # `mask` coming in as other types is often an error and should fail the model.
     value_cast = op.CastLike(value, self)
-    return op.Where(mask_cast, value_cast, self)
+    return op.Where(mask, value_cast, self)
 
 
 def aten_masked_scatter(self: TensorType, mask: TensorType, source: TensorType) -> TensorType: