diff --git a/onnxslim/onnx_graphsurgeon/exporters/onnx_exporter.py b/onnxslim/onnx_graphsurgeon/exporters/onnx_exporter.py
index cc4f329..2f447e0 100644
--- a/onnxslim/onnx_graphsurgeon/exporters/onnx_exporter.py
+++ b/onnxslim/onnx_graphsurgeon/exporters/onnx_exporter.py
@@ -337,19 +337,19 @@ def export_onnx(graph: Graph, do_type_check=True, **kwargs) -> "onnx.ModelProto"
     """
     sub_graphs = graph.subgraphs(recursive=True)
 
-    graph_constants_list = []
-    for sub_graph in sub_graphs:
-        graph_constants = {name: tensor for name, tensor in sub_graph.tensors().items() if isinstance(tensor, Constant)}
-        graph_constants_list.append(graph_constants)
+    graph_constants_list = [
+        {name: tensor for name, tensor in sub_graph.tensors().items() if isinstance(tensor, Constant)}
+        for sub_graph in sub_graphs
+    ]
 
     if not graph_constants_list:
         intersection = None
     else:
-        intersection = {
-            k: graph_constants_list[0][k]
-            for k in graph_constants_list[0]
-            if all(k in d for d in graph_constants_list[1:])
-        }
+        intersection = (
+            {key: graph_constants_list[0][key] for key in graph_constants_list[0]
+            if all(key in d and graph_constants_list[0][key] == d[key] for d in graph_constants_list[1:])}
+            if graph_constants_list else None
+        )
 
     onnx_graph = OnnxExporter.export_graph(
         graph, tensor_map=intersection, subgraph_tensor_map=intersection, do_type_check=do_type_check
diff --git a/onnxslim/onnx_graphsurgeon/ir/graph.py b/onnxslim/onnx_graphsurgeon/ir/graph.py
index 64ab7c2..58c4637 100644
--- a/onnxslim/onnx_graphsurgeon/ir/graph.py
+++ b/onnxslim/onnx_graphsurgeon/ir/graph.py
@@ -780,7 +780,7 @@ def should_exclude_node(node):
         for tensor in self.tensors().values():
             if len(tensor.inputs) == 1:
                 node = tensor.inputs[0]
-                if node.op == "Constant":
+                if node.op == "Constant" and tensor.outputs:
                     if len(node.attrs) != 1:
                         G_LOGGER.warning("Constant node must contain exactly one attribute")
                         continue
@@ -1227,7 +1227,7 @@ def should_eval_foldable(tensor):
             graph_tensors = self.tensors()
             for name, values in constant_values.items():
                 tensor = graph_tensors[name]
-                if isinstance(tensor, Constant):
+                if isinstance(tensor, Constant) or not tensor.outputs:
                     # No need to fold tensors that are already constant.
                     continue