diff --git a/lib/Conversion/TorchOnnxToTorch/DefaultDomainAtoF.cpp b/lib/Conversion/TorchOnnxToTorch/DefaultDomainAtoF.cpp
index 785c631c1..c976b4984 100644
--- a/lib/Conversion/TorchOnnxToTorch/DefaultDomainAtoF.cpp
+++ b/lib/Conversion/TorchOnnxToTorch/DefaultDomainAtoF.cpp
@@ -1495,23 +1495,34 @@ void mlir::torch::onnx_c::populateDefaultDomainAtoF(
   patterns.onOp(
       "Expand", 1, [](OpBinder binder, ConversionPatternRewriter &rewriter) {
         // uses ideas and code from onnx.Reshape
+        auto loc = binder.getLoc();
         Torch::ValueTensorType resultType;
         Value data, shape;
         if (binder.tensorOperands(data, shape) ||
             binder.tensorResultType(resultType))
           return failure();
-        Torch::BaseTensorType shapeType =
-            shape.getType().cast<Torch::BaseTensorType>();
+
+        auto dataType = cast<Torch::BaseTensorType>(data.getType());
+        auto shapeType = cast<Torch::BaseTensorType>(shape.getType());
+        if (!dataType.hasSizes() || !shapeType.hasSizes())
+          return failure();
+
+        auto shapeSizes = shapeType.getSizes();
+        int64_t dataRank = dataType.getSizes().size();
+        int64_t shapeRank = shapeSizes.size();
+        if (shapeRank != 1 || shapeSizes[0] == Torch::kUnknownSize)
+          return failure();
+
+        auto rankDifference = dataRank - shapeSizes[0];
+
         SmallVector<int64_t> selectSizes;
         Type selectResultType = shapeType.getWithSizesAndDtype(
             llvm::ArrayRef(selectSizes), shapeType.getOptionalDtype());
         // Variable to store 1-D onnx shape tensor, shapeSizes[0] has the
         // dimension size
-        auto shapeSizes =
-            dyn_cast<Torch::ValueTensorType>(shape.getType()).getSizes();
         // A constant zero value
         Value zero = rewriter.create<Torch::ConstantIntOp>(
-            binder.getLoc(), rewriter.getI64IntegerAttr(0));
+            loc, rewriter.getI64IntegerAttr(0));
         // Variable to store pytorch int list of shape (dimension)
         SmallVector<Value> dimList;
 
@@ -1520,12 +1531,21 @@ void mlir::torch::onnx_c::populateDefaultDomainAtoF(
         // takes list of int
         for (int i = 0; i < shapeSizes[0]; i++) {
           Value selectIndex = rewriter.create<Torch::ConstantIntOp>(
-              binder.getLoc(), rewriter.getType<Torch::IntType>(),
+              loc, rewriter.getType<Torch::IntType>(),
               rewriter.getIntegerAttr(rewriter.getIntegerType(64), i));
           Value extract = rewriter.create<Torch::AtenSelectIntOp>(
-              binder.getLoc(), selectResultType, shape, zero, selectIndex);
+              loc, selectResultType, shape, zero, selectIndex);
           Value dim = rewriter.create<Torch::AtenItemOp>(
-              binder.getLoc(), rewriter.getType<Torch::IntType>(), extract);
+              loc, rewriter.getType<Torch::IntType>(), extract);
+
+          if (i + rankDifference >= 0) {
+            Value iv =
+                rewriter.create<Torch::ConstantIntOp>(loc, i + rankDifference);
+            auto sz = rewriter.create<Torch::AtenSizeIntOp>(
+                loc, rewriter.getType<Torch::IntType>(), data, iv);
+            dim = rewriter.create<Torch::PrimMaxIntOp>(loc, dim, sz);
+          }
+
           dimList.push_back(dim);
         }
         Value dimValueList = rewriter.create<Torch::PrimListConstructOp>(
diff --git a/projects/pt1/e2e_testing/xfail_sets.py b/projects/pt1/e2e_testing/xfail_sets.py
index 695b51c18..dd4976018 100644
--- a/projects/pt1/e2e_testing/xfail_sets.py
+++ b/projects/pt1/e2e_testing/xfail_sets.py
@@ -1507,8 +1507,6 @@ ONNX_XFAIL_SET = {
     "ArangeStartOutDtypeModule_basic",
     "ArangeStartOutViewModule_basic",
     "BroadcastDynamicDimModule_basic",
-    "BroadcastToModule_basic",
-    "ExpandModule_basic",
     "MoveDimIntNegativeIndexModule_basic",
     "ViewSizeFromOtherTensor_basic",
 
diff --git a/test/Conversion/TorchOnnxToTorch/simple_ops_a_to_f.mlir b/test/Conversion/TorchOnnxToTorch/simple_ops_a_to_f.mlir
index 2c013553b..1e816a38e 100644
--- a/test/Conversion/TorchOnnxToTorch/simple_ops_a_to_f.mlir
+++ b/test/Conversion/TorchOnnxToTorch/simple_ops_a_to_f.mlir
@@ -1164,15 +1164,21 @@ func.func @test_exp(%arg0: !torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f3
 // CHECK-LABEL: @test_expand_dim2_shape2
 func.func @test_expand_dim2_shape2(%arg0: !torch.vtensor<[1,4],f32>, %arg1: !torch.vtensor<[2],si32>)
               -> !torch.vtensor<[3,4],f32> attributes {torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 18 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
-  // CHECK: %[[INT0:.+]] = torch.constant.int 0
-  // CHECK: %[[INT0_0:.+]] = torch.constant.int 0
-  // CHECK: torch.aten.select.int %arg1, %int0, %int0_0 : !torch.vtensor<[2],si32>, !torch.int, !torch.int -> !torch.vtensor<[],si32>
-  // CHECK: torch.aten.item %0 : !torch.vtensor<[],si32> -> !torch.int
-  // CHECK: %[[INT1:.+]] = torch.constant.int 1
-  // CHECK: torch.aten.select.int %arg1, %int0, %int1 : !torch.vtensor<[2],si32>, !torch.int, !torch.int -> !torch.vtensor<[],si32>
-  // CHECK: torch.aten.item %2 : !torch.vtensor<[],si32> -> !torch.int
-  // CHECK: torch.prim.ListConstruct %1, %3 : (!torch.int, !torch.int) -> !torch.list<int>
-  // CHECK: torch.aten.broadcast_to %arg0, %4 : !torch.vtensor<[1,4],f32>, !torch.list<int> -> !torch.vtensor<[3,4],f32>
+  // CHECK-DAG: %[[INT0:.+]] = torch.constant.int 0
+  // CHECK-DAG: %[[INT0_0:.+]] = torch.constant.int 0
+  // CHECK-DAG: %[[SEL0:.+]] = torch.aten.select.int %arg1, %[[INT0]], %[[INT0_0]] : !torch.vtensor<[2],si32>, !torch.int, !torch.int -> !torch.vtensor<[],si32>
+  // CHECK-DAG: %[[ITEM0:.+]] = torch.aten.item %[[SEL0]] : !torch.vtensor<[],si32> -> !torch.int
+  // CHECK-DAG: %[[I0:.+]] = torch.constant.int 0
+  // CHECK-DAG: %[[SZ0:.+]] = torch.aten.size.int %arg0, %[[I0]] : !torch.vtensor<[1,4],f32>, !torch.int -> !torch.int
+  // CHECK-DAG: %[[MX0:.+]] = torch.prim.max.int %[[ITEM0]], %[[SZ0]] : !torch.int, !torch.int -> !torch.int
+  // CHECK-DAG: %[[INT1:.+]] = torch.constant.int 1
+  // CHECK-DAG: %[[SEL1:.+]] = torch.aten.select.int %arg1, %[[INT0]], %[[INT1]] : !torch.vtensor<[2],si32>, !torch.int, !torch.int -> !torch.vtensor<[],si32>
+  // CHECK-DAG: %[[ITEM1:.+]] = torch.aten.item %[[SEL1]] : !torch.vtensor<[],si32> -> !torch.int
+  // CHECK-DAG: %[[I1:.+]] = torch.constant.int 1
+  // CHECK-DAG: %[[SZ1:.+]] = torch.aten.size.int %arg0, %[[I1]] : !torch.vtensor<[1,4],f32>, !torch.int -> !torch.int
+  // CHECK-DAG: %[[MX1:.+]] = torch.prim.max.int %[[ITEM1]], %[[SZ1]] : !torch.int, !torch.int -> !torch.int
+  // CHECK: %[[LIST:.+]] = torch.prim.ListConstruct %[[MX0]], %[[MX1]] : (!torch.int, !torch.int) -> !torch.list<int>
+  // CHECK: torch.aten.broadcast_to %arg0, %[[LIST]] : !torch.vtensor<[1,4],f32>, !torch.list<int> -> !torch.vtensor<[3,4],f32>
   %0 = torch.operator "onnx.Expand"(%arg0, %arg1) : (!torch.vtensor<[1,4],f32>, !torch.vtensor<[2],si32>) -> !torch.vtensor<[3,4],f32>
   return %0 : !torch.vtensor<[3,4],f32>
 }
@@ -1181,47 +1187,31 @@ func.func @test_expand_dim2_shape2(%arg0: !torch.vtensor<[1,4],f32>, %arg1: !tor
 
 // CHECK-LABEL: @test_expand_dim2_shape3
 func.func @test_expand_dim2_shape3(%arg0: !torch.vtensor<[3,1],f32>, %arg1: !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,3,6],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
-  // CHECK: %[[INT0:.+]] = torch.constant.int 0
-  // CHECK: %[[INT0_0:.+]] = torch.constant.int 0
-  // CHECK: torch.aten.select.int %arg1, %int0, %int0_0 : !torch.vtensor<[3],si64>, !torch.int, !torch.int -> !torch.vtensor<[],si64>
-  // CHECK: torch.aten.item %0 : !torch.vtensor<[],si64> -> !torch.int
-  // CHECK: %[[INT1:.+]] = torch.constant.int 1
-  // CHECK: torch.aten.select.int %arg1, %int0, %int1 : !torch.vtensor<[3],si64>, !torch.int, !torch.int -> !torch.vtensor<[],si64>
-  // CHECK: torch.aten.item %2 : !torch.vtensor<[],si64> -> !torch.int
-  // CHECK: %[[INT2:.+]] = torch.constant.int 2
-  // CHECK: torch.aten.select.int %arg1, %int0, %int2 : !torch.vtensor<[3],si64>, !torch.int, !torch.int -> !torch.vtensor<[],si64>
-  // CHECK: torch.aten.item %4 : !torch.vtensor<[],si64> -> !torch.int
-  // CHECK: torch.prim.ListConstruct %1, %3, %5 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int>
-  // CHECK: torch.aten.broadcast_to %arg0, %6 : !torch.vtensor<[3,1],f32>, !torch.list<int> -> !torch.vtensor<[2,3,6],f32>
+  // CHECK:  %[[I0:.+]] = torch.constant.int 0
+  // CHECK-NEXT:  %[[I0_0:.+]] = torch.constant.int 0
+  // CHECK-NEXT:  %[[SEL0:.+]] = torch.aten.select.int %arg1, %[[I0]], %[[I0_0]]
+  // CHECK-NEXT:  %[[ITEM0:.+]] = torch.aten.item %[[SEL0]]
+  // CHECK-NEXT:  %[[I1:.+]] = torch.constant.int 1
+  // CHECK-NEXT:  %[[SEL1:.+]] = torch.aten.select.int %arg1, %[[I0]], %[[I1]]
+  // CHECK-NEXT:  %[[ITEM1:.+]] = torch.aten.item %[[SEL1]]
+  // CHECK-NEXT:  %[[D1:.+]] = torch.constant.int 0
+  // CHECK-NEXT:  %[[SZ1:.+]] = torch.aten.size.int %arg0, %[[D1]]
+  // CHECK-NEXT:  %[[MX1:.+]] = torch.prim.max.int %[[ITEM1]], %[[SZ1]] : !torch.int, !torch.int -> !torch.int
+  // CHECK-NEXT:  %[[I2:.+]] = torch.constant.int 2
+  // CHECK-NEXT:  %[[SEL2:.+]] = torch.aten.select.int %arg1, %[[I0]], %[[I2]]
+  // CHECK-NEXT:  %[[ITEM2:.+]] = torch.aten.item %[[SEL2]]
+  // CHECK-NEXT:  %[[D2:.+]] = torch.constant.int 1
+  // CHECK-NEXT:  %[[SZ2:.+]] = torch.aten.size.int %arg0, %[[D2]]
+  // CHECK-NEXT:  %[[MX2:.+]] = torch.prim.max.int %[[ITEM2]], %[[SZ2]]
+  // CHECK-NEXT:  %[[LIST:.+]] = torch.prim.ListConstruct %[[ITEM0]], %[[MX1]], %[[MX2]]
+  // CHECK-NEXT:  %[[EXPAND:.+]] = torch.aten.broadcast_to %arg0, %[[LIST]]
+  // CHECK:  return %[[EXPAND]]
   %0 = torch.operator "onnx.Expand"(%arg0, %arg1) : (!torch.vtensor<[3,1],f32>, !torch.vtensor<[3],si64>) -> !torch.vtensor<[2,3,6],f32>
   return %0 : !torch.vtensor<[2,3,6],f32>
 }
 
 // -----
 
-// CHECK-LABEL: @test_expand_dim3_shape4
-func.func @test_expand_dim3_shape4(%arg0: !torch.vtensor<[1,3,1],f32>, %arg1: !torch.vtensor<[4],si64>) -> !torch.vtensor<[3,3,3,3],f32> attributes {torch.onnx_meta.ir_version = 4 : si64, torch.onnx_meta.opset_version = 9 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
-  // CHECK: %[[INT0:.+]] = torch.constant.int 0
-  // CHECK: %[[INT0_0:.+]] = torch.constant.int 0
-  // CHECK: torch.aten.select.int %arg1, %int0, %int0_0 : !torch.vtensor<[4],si64>, !torch.int, !torch.int -> !torch.vtensor<[],si64>
-  // CHECK: torch.aten.item %0 : !torch.vtensor<[],si64> -> !torch.int
-  // CHECK: %[[INT1:.+]] = torch.constant.int 1
-  // CHECK: torch.aten.select.int %arg1, %int0, %int1 : !torch.vtensor<[4],si64>, !torch.int, !torch.int -> !torch.vtensor<[],si64>
-  // CHECK: torch.aten.item %2 : !torch.vtensor<[],si64> -> !torch.int
-  // CHECK: %[[INT2:.+]] = torch.constant.int 2
-  // CHECK: torch.aten.select.int %arg1, %int0, %int2 : !torch.vtensor<[4],si64>, !torch.int, !torch.int -> !torch.vtensor<[],si64>
-  // CHECK: torch.aten.item %4 : !torch.vtensor<[],si64> -> !torch.int
-  // CHECK: %[[INT3:.+]] = torch.constant.int 3
-  // CHECK: torch.aten.select.int %arg1, %int0, %int3 : !torch.vtensor<[4],si64>, !torch.int, !torch.int -> !torch.vtensor<[],si64>
-  // CHECK: torch.aten.item %6 : !torch.vtensor<[],si64> -> !torch.int
-  // CHECK: torch.prim.ListConstruct %1, %3, %5, %7 : (!torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list<int>
-  // CHECK: %9 = torch.aten.broadcast_to %arg0, %8 : !torch.vtensor<[1,3,1],f32>, !torch.list<int> -> !torch.vtensor<[3,3,3,3],f32>
-  %0 = torch.operator "onnx.Expand"(%arg0, %arg1) : (!torch.vtensor<[1,3,1],f32>, !torch.vtensor<[4],si64>) -> !torch.vtensor<[3,3,3,3],f32>
-  return %0 : !torch.vtensor<[3,3,3,3],f32>
-}
-
-// -----
-
 // CHECK-LABEL: @test_dropout
 func.func @test_dropout(%arg0: !torch.vtensor<[3],f32>) -> !torch.vtensor<[3],f32> attributes {torch.onnx_meta.ir_version = 7 : si64, torch.onnx_meta.opset_version = 13 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
   // CHECK: torch.aten.dropout %arg0, %float5.000000e-01, %false : !torch.vtensor<[3],f32>, !torch.float, !torch.bool -> !torch.vtensor<[3],f32