diff --git a/include/torch-mlir/Dialect/Torch/IR/GeneratedTorchOps.td b/include/torch-mlir/Dialect/Torch/IR/GeneratedTorchOps.td
index 82d11ec0737a..fbe7b31e2925 100644
--- a/include/torch-mlir/Dialect/Torch/IR/GeneratedTorchOps.td
+++ b/include/torch-mlir/Dialect/Torch/IR/GeneratedTorchOps.td
@@ -18969,6 +18969,31 @@ def Torch_PrimsSumOp : Torch_Op<"prims.sum", [
   }];
 }
 
+def Torch_PrimsXorSumOp : Torch_Op<"prims.xor_sum", [
+    AllowsTypeRefinement,
+    HasValueSemantics,
+    ReadOnly
+  ]> {
+  let summary = "Generated op for `prims::xor_sum : (Tensor, int[]?, int?) -> (Tensor)`";
+  let arguments = (ins
+    AnyTorchTensorType:$inp,
+    AnyTorchOptionalListOfTorchIntType:$dims,
+    AnyTorchOptionalIntType:$output_dtype
+  );
+  let results = (outs
+    AnyTorchOptionalTensorType:$result
+  );
+  let hasCustomAssemblyFormat = 1;
+  let extraClassDefinition = [{
+    ParseResult PrimsXorSumOp::parse(OpAsmParser &parser, OperationState &result) {
+      return parseDefaultTorchOp(parser, result, 3, 1);
+    }
+    void PrimsXorSumOp::print(OpAsmPrinter &printer) {
+      printDefaultTorchOp(printer, *this, 3, 1);
+    }
+  }];
+}
+
 def Torch_PrimsViewOfOp : Torch_Op<"prims.view_of", [
     AllowsTypeRefinement,
     ReadOnly
diff --git a/lib/Conversion/TorchToStablehlo/Reduction.cpp b/lib/Conversion/TorchToStablehlo/Reduction.cpp
index 82c9d4659461..b9e1929c78da 100644
--- a/lib/Conversion/TorchToStablehlo/Reduction.cpp
+++ b/lib/Conversion/TorchToStablehlo/Reduction.cpp
@@ -47,7 +47,7 @@ static Value createInitialValueForReduceOp(Operation *op, Type elementTy,
   auto constType = RankedTensorType::get({}, elementTy);
   DenseElementsAttr constAttr = nullptr;
   if (isa<AtenSumOp, AtenSumDimIntListOp, AtenFrobeniusNormDimOp,
-          AtenLinalgVectorNormOp>(op)) {
+          AtenLinalgVectorNormOp, PrimsXorSumOp>(op)) {
     if (isa<mlir::FloatType>(elementTy)) {
       constAttr = DenseElementsAttr::get(
           constType, {APFloat::getZero(
@@ -157,6 +157,9 @@ static Value createReduceOpWithSingleRegionOp(Operation *op, Value input,
     } else if (isa<AtenProdOp, AtenProdDimIntOp>(op)) {
       result = stablehlo::MulOp::create(rewriter, op->getLoc(), blockArgumentTy,
                                         *firstArgument, *secondArgument);
+    } else if (isa<PrimsXorSumOp>(op)) {
+      result = stablehlo::XorOp::create(rewriter, op->getLoc(), blockArgumentTy,
+                                        *firstArgument, *secondArgument);
     } else {
       op->emitError("unimplemented lowering in "
                     "createReduceOpWithSingleRegionOp");
@@ -756,6 +759,64 @@ LogicalResult ConvertAtenReductionOp<AtenSumDimIntListOp>::matchAndRewrite(
 }
 } // namespace
 
+// PrimsXorSumOp
+namespace {
+template <>
+LogicalResult ConvertAtenReductionOp<PrimsXorSumOp>::matchAndRewrite(
+    PrimsXorSumOp op, OpAdaptor adaptor,
+    ConversionPatternRewriter &rewriter) const {
+  Value input = adaptor.getInp();
+  auto inputTy = dyn_cast<RankedTensorType>(input.getType());
+  auto outTy =
+      dyn_cast<RankedTensorType>(getTypeConverter()->convertType(op.getType()));
+  if (!inputTy || !outTy) {
+    return rewriter.notifyMatchFailure(
+        op, "only Tensor types supported in StableHLO");
+  }
+
+  auto inputElemTy = inputTy.getElementType();
+  if (!isa<mlir::IntegerType>(inputElemTy)) {
+    return rewriter.notifyMatchFailure(
+        op, "XOR reduction requires integer element type");
+  }
+
+  SmallVector<int64_t> inputDims;
+  SmallVector<int64_t> dims;
+  if (failed(checkNotNone(rewriter, op, op.getDims()))) {
+    inputDims = llvm::to_vector<4>(llvm::seq<int64_t>(0, inputTy.getRank()));
+  } else {
+    if (!matchPattern(op.getDims(), m_TorchListOfConstantInts(inputDims))) {
+      return rewriter.notifyMatchFailure(
+          op, "non-const integer `dims` is not supported");
+    }
+    if (inputDims.empty()) {
+      inputDims = llvm::to_vector<4>(llvm::seq<int64_t>(0, inputTy.getRank()));
+    }
+  }
+  for (auto d : inputDims) {
+    d = toPositiveDim(d, inputTy.getRank());
+    if (isValidDim(d, inputTy.getRank())) {
+      dims.push_back(d);
+    }
+  }
+  llvm::sort(dims.begin(), dims.end());
+
+  SmallVector<int64_t> reduceResultShape =
+      getReduceOutputShape(inputTy.getShape(), dims);
+
+  Value reduceResult = createReduceOpWithSingleRegionOp(
+      op, input,
+      RankedTensorType::get(reduceResultShape, outTy.getElementType()), dims,
+      rewriter, /*allowNonFinites=*/false);
+  if (!reduceResult) {
+    return op->emitError("createReduceOpWithSingleRegionOp return nullptr");
+  }
+
+  rewriter.replaceOp(op, reduceResult);
+  return success();
+}
+} // namespace
+
 // AtenProdDimIntOp
 namespace {
 template <>
@@ -1003,6 +1064,7 @@ void mlir::torch::torch_to_stablehlo::populateReductionOpPatternsAndLegality(
   INSERT_ATEN_REDUCTION_OP_PATTERN(AtenFrobeniusNormDimOp);
   INSERT_ATEN_REDUCTION_OP_PATTERN(AtenLinalgVectorNormOp);
   INSERT_ATEN_REDUCTION_OP_PATTERN(AtenProdDimIntOp);
+  INSERT_ATEN_REDUCTION_OP_PATTERN(PrimsXorSumOp);
 #undef INSERT_ATEN_REDUCTION_OP_PATTERN
 
 #define INSERT_ATEN_REDUCTION_ALL_DIMS_OP_PATTERN(AtenOp)                      \
diff --git a/projects/pt1/python/torch_mlir/jit_ir_importer/build_tools/torch_ods_gen.py b/projects/pt1/python/torch_mlir/jit_ir_importer/build_tools/torch_ods_gen.py
index 7d5e65c21cef..2e00a01e9755 100644
--- a/projects/pt1/python/torch_mlir/jit_ir_importer/build_tools/torch_ods_gen.py
+++ b/projects/pt1/python/torch_mlir/jit_ir_importer/build_tools/torch_ods_gen.py
@@ -1319,6 +1319,7 @@ def emit_with_mutating_variants(key, **kwargs):
     emit("prims::split_dim : (Tensor, int, int) -> (Tensor)")
     emit("prims::squeeze : (Tensor, int[]) -> (Tensor)")
     emit("prims::sum : (Tensor, int[]?, int?) -> (Tensor)")
+    emit("prims::xor_sum : (Tensor, int[]?, int?) -> (Tensor)")
     emit("prims::view_of : (Tensor) -> (Tensor)", has_folder=True)
     emit("prims::iota : (int, int, int, int, Device, bool) -> (Tensor)")
 
diff --git a/test/Conversion/TorchToStablehlo/reduction.mlir b/test/Conversion/TorchToStablehlo/reduction.mlir
index 924f17f4c9b1..730ce9b37bd9 100644
--- a/test/Conversion/TorchToStablehlo/reduction.mlir
+++ b/test/Conversion/TorchToStablehlo/reduction.mlir
@@ -31,3 +31,20 @@ func.func @torch.aten.prod.intdim_negative_dim(%arg0: !torch.vtensor<[?,?,?,?],f
   // CHECK: return %[[VAL_3]] : !torch.vtensor<[?,?,?],f32>
   return %0 : !torch.vtensor<[?,?,?],f32>
 }
+
+// -----
+
+// CHECK-LABEL: @torch.prims.xor_sum(
+// CHECK-SAME:    %[[ARG0:.*]]: !torch.vtensor<[4],si32>) -> !torch.vtensor<[],si32> {
+// CHECK:   %[[INPUT:.*]] = torch_c.to_builtin_tensor %[[ARG0]] : !torch.vtensor<[4],si32> -> tensor<4xi32>
+// CHECK:   %[[INIT:.*]] = stablehlo.constant dense<0> : tensor<i32>
+// CHECK:   %[[REDUCE:.*]] = stablehlo.reduce(%[[INPUT]] init: %[[INIT]]) applies stablehlo.xor across dimensions = [0] : (tensor<4xi32>, tensor<i32>) -> tensor<i32>
+// CHECK:   %[[OUT:.*]] = torch_c.from_builtin_tensor %[[REDUCE]] : tensor<i32> -> !torch.vtensor<[],si32>
+// CHECK:   return %[[OUT]] : !torch.vtensor<[],si32>
+func.func @torch.prims.xor_sum(%arg0: !torch.vtensor<[4],si32>) -> !torch.vtensor<[],si32> {
+  %int0 = torch.constant.int 0
+  %dims = torch.prim.ListConstruct %int0 : (!torch.int) -> !torch.list<int>
+  %none = torch.constant.none
+  %0 = torch.prims.xor_sum %arg0, %dims, %none : !torch.vtensor<[4],si32>, !torch.list<int>, !torch.none -> !torch.vtensor<[],si32>
+  return %0 : !torch.vtensor<[],si32>
+}