diff --git a/lib/Conversion/TorchOnnxToTorch/DefaultDomainAtoF.cpp b/lib/Conversion/TorchOnnxToTorch/DefaultDomainAtoF.cpp
index 2e3f3e8b8053..f998240b3472 100644
--- a/lib/Conversion/TorchOnnxToTorch/DefaultDomainAtoF.cpp
+++ b/lib/Conversion/TorchOnnxToTorch/DefaultDomainAtoF.cpp
@@ -306,7 +306,7 @@ void mlir::torch::onnx_c::populateDefaultDomainAtoF(
                   return success();
                 });
   patterns.onOp(
-      "AveragePool", 19,
+      "AveragePool", 11,
       [](OpBinder binder, ConversionPatternRewriter &rewriter) {
         std::string autoPad;
         SmallVector<int64_t> dilation;
@@ -357,7 +357,8 @@ void mlir::torch::onnx_c::populateDefaultDomainAtoF(
               binder.op,
               "padding list size does not match twice the number of axes");
         }
-        if (binder.s64IntegerArrayAttr(strides, "strides", {1})) {
+        if (binder.s64IntegerArrayAttr(
+                strides, "strides", llvm::SmallVector<int64_t>(rank - 2, 1))) {
           return failure();
         }
         if (strides.size() != 1 && strides.size() != rank - 2) {
diff --git a/lib/Conversion/TorchToLinalg/Pooling.cpp b/lib/Conversion/TorchToLinalg/Pooling.cpp
index e795d2ea9fb8..283ac42ca6c5 100644
--- a/lib/Conversion/TorchToLinalg/Pooling.cpp
+++ b/lib/Conversion/TorchToLinalg/Pooling.cpp
@@ -114,8 +114,22 @@ static Value padInputTensor(Operation *op, ConversionPatternRewriter &rewriter,
                             SmallVectorImpl<int64_t> &paddingInts,
                             Value initValue) {
   SmallVector<int64_t> lowPaddingIncludingNC = {0, 0};
-  lowPaddingIncludingNC.append(paddingInts);
-  SmallVector<int64_t> highPaddingIncludingNC = lowPaddingIncludingNC;
+  SmallVector<int64_t> highPaddingIncludingNC = {0, 0};
+
+  unsigned selfRank = self.getType().cast<RankedTensorType>().getRank();
+  unsigned paddingIntsSize = paddingInts.size();
+
+  if (paddingIntsSize == 2 * (selfRank - 2)) {
+    // This condition being true means that the `paddingInts` contain seperate
+    // values for low padding and high padding.
+    for (unsigned i = 0; i < paddingIntsSize / 2; i++)
+      lowPaddingIncludingNC.push_back(paddingInts[i]);
+    for (unsigned i = paddingIntsSize / 2; i < paddingIntsSize; i++)
+      highPaddingIncludingNC.push_back(paddingInts[i]);
+  } else {
+    lowPaddingIncludingNC.append(paddingInts);
+    highPaddingIncludingNC = lowPaddingIncludingNC;
+  }
 
   if (ceilMode) {
     for (int64_t i = 0; i < dimensionality; ++i) {
diff --git a/projects/pt1/e2e_testing/xfail_sets.py b/projects/pt1/e2e_testing/xfail_sets.py
index 671df14b3d34..5d9db7558d80 100644
--- a/projects/pt1/e2e_testing/xfail_sets.py
+++ b/projects/pt1/e2e_testing/xfail_sets.py
@@ -2044,17 +2044,7 @@
     "LinalgNormModule_basic",
 
     # Failure - onnx_lowering: onnx.AveragePool
-    "AdaptiveAvgPool1dNonUnitOutputSizeStaticModule_basic",
-    "AdaptiveAvgPool1dStaticEvenMultiple_basic",
-    "AdaptiveAvgPool2dNonUnitOutputSizeStaticModule_basic",
-    "AvgPool1dFloatModule_basic",
-    "AvgPool1dIntModule_basic",
-    "AvgPool1dStaticModule_basic",
-    "AvgPool2dCeilModeTrueModule_basic",
     "AvgPool2dDivisorOverrideModule_basic",
-    "AvgPool2dFloatModule_basic",
-    "AvgPool2dIntModule_basic",
-    "AvgPool2dStaticModule_basic",
 
     # Failure - onnx_lowering: onnx.Cast
     "BucketizeTensorOutInt32RightModule_basic",