diff --git a/test/cpp/test_aten_xla_tensor.cpp b/test/cpp/test_aten_xla_tensor.cpp
index 162d496fc597..dfecb8a83b7b 100644
--- a/test/cpp/test_aten_xla_tensor.cpp
+++ b/test/cpp/test_aten_xla_tensor.cpp
@@ -1099,6 +1099,18 @@ TEST_F(AtenXlaTensorTest, TestArgMinSameValue) {
   });
 }
 
+TEST_F(AtenXlaTensorTest, TestArgMinWrapper) {
+  at::Tensor a = at::rand({4, 4, 4}, at::TensorOptions(at::kFloat));
+  for (int dim : {1, -2}) {
+    at::Tensor b = at::_argmin(a, dim, /*keepdim=*/false);
+    ForEachDevice([&](const Device& device) {
+      at::Tensor xla_a = bridge::CreateXlaTensor(a, device);
+      at::Tensor xla_b = at::_argmin(xla_a, dim, /*keepdim=*/false);
+      AllClose(b, xla_b);
+    });
+  }
+}
+
 TEST_F(AtenXlaTensorTest, TestArgMax) {
   at::Tensor a = at::rand({4, 4, 4}, at::TensorOptions(at::kFloat));
   at::Tensor b = at::argmax(a);
@@ -1143,6 +1155,18 @@ TEST_F(AtenXlaTensorTest, TestArgMaxSameValue) {
   });
 }
 
+TEST_F(AtenXlaTensorTest, TestArgMaxWrapper) {
+  at::Tensor a = at::rand({4, 4, 4}, at::TensorOptions(at::kFloat));
+  for (int dim : {1, -2}) {
+    at::Tensor b = at::_argmax(a, dim, /*keepdim=*/false);
+    ForEachDevice([&](const Device& device) {
+      at::Tensor xla_a = bridge::CreateXlaTensor(a, device);
+      at::Tensor xla_b = at::_argmax(xla_a, dim, /*keepdim=*/false);
+      AllClose(b, xla_b);
+    });
+  }
+}
+
 TEST_F(AtenXlaTensorTest, TestAsin) {
   at::Tensor a = at::rand({2, 2}, at::TensorOptions(at::kFloat));
   at::Tensor b = at::asin(a);
@@ -1497,6 +1521,18 @@ TEST_F(AtenXlaTensorTest, TestMatmulBcast) {
   });
 }
 
+TEST_F(AtenXlaTensorTest, TestDot) {
+  at::Tensor a = at::rand({4}, at::TensorOptions(at::kFloat));
+  at::Tensor b = at::rand({4}, at::TensorOptions(at::kFloat));
+  at::Tensor c = at::dot(a, b);
+  ForEachDevice([&](const Device& device) {
+    at::Tensor xla_a = bridge::CreateXlaTensor(a, device);
+    at::Tensor xla_b = bridge::CreateXlaTensor(b, device);
+    at::Tensor xla_c = at::dot(xla_a, xla_b);
+    AllClose(c, xla_c);
+  });
+}
+
 TEST_F(AtenXlaTensorTest, TestBatchMatMul) {
   at::Tensor a = at::rand({3, 6, 4}, at::TensorOptions(at::kFloat));
   at::Tensor b = at::rand({3, 4, 5}, at::TensorOptions(at::kFloat));
diff --git a/torch_xla/csrc/aten_xla_type.cpp b/torch_xla/csrc/aten_xla_type.cpp
index 1db254dc8b9a..039a16b8c206 100644
--- a/torch_xla/csrc/aten_xla_type.cpp
+++ b/torch_xla/csrc/aten_xla_type.cpp
@@ -1401,6 +1401,15 @@ at::Tensor AtenXlaType::bmm(const at::Tensor& self,
       XLATensor::bmm(bridge::GetXlaTensor(self), bridge::GetXlaTensor(mat2)));
 }
 
+at::Tensor AtenXlaType::dot(const at::Tensor& self,
+                            const at::Tensor& tensor) const {
+  XLA_CHECK_EQ(self.dim(), 1)
+      << "dot: Expected 1-D argument self, but got " << self.dim() << "-D";
+  XLA_CHECK_EQ(tensor.dim(), 1)
+      << "dot: Expected 1-D argument tensor, but got " << tensor.dim() << "-D";
+  return matmul(self, tensor);
+}
+
 std::vector<at::Tensor> AtenXlaType::broadcast_tensors(
     at::TensorList tensors) const {
   return bridge::AtenFromXlaTensors(
@@ -1787,6 +1796,11 @@ at::Tensor AtenXlaType::argmax(const at::Tensor& self, int64_t dim,
       XLATensor::argmax(bridge::GetXlaTensor(self), dim, keepdim));
 }
 
+at::Tensor AtenXlaType::_argmax(const at::Tensor& self, int64_t dim,
+                                bool keepdim) const {
+  return at::native::_argmax(self, dim, keepdim);
+}
+
 at::Tensor AtenXlaType::argmax(const at::Tensor& self) const {
   return bridge::AtenFromXlaTensor(
       XLATensor::argmax(bridge::GetXlaTensor(self)));
@@ -1798,6 +1812,11 @@ at::Tensor AtenXlaType::argmin(const at::Tensor& self, int64_t dim,
       XLATensor::argmin(bridge::GetXlaTensor(self), dim, keepdim));
 }
 
+at::Tensor AtenXlaType::_argmin(const at::Tensor& self, int64_t dim,
+                                bool keepdim) const {
+  return at::native::_argmin(self, dim, keepdim);
+}
+
 at::Tensor AtenXlaType::argmin(const at::Tensor& self) const {
   return bridge::AtenFromXlaTensor(
       XLATensor::argmin(bridge::GetXlaTensor(self)));
diff --git a/torch_xla/csrc/aten_xla_type.h b/torch_xla/csrc/aten_xla_type.h
index 594de8824e97..1bd7a060f1df 100644
--- a/torch_xla/csrc/aten_xla_type.h
+++ b/torch_xla/csrc/aten_xla_type.h
@@ -429,6 +429,9 @@ class AtenXlaType : public AtenXlaTypeBase {
 
   at::Tensor bmm(const at::Tensor& self, const at::Tensor& mat2) const override;
 
+  at::Tensor dot(const at::Tensor& self,
+                 const at::Tensor& tensor) const override;
+
   std::vector<at::Tensor> broadcast_tensors(
       at::TensorList tensors) const override;
 
@@ -562,10 +565,14 @@ class AtenXlaType : public AtenXlaTypeBase {
   at::Tensor argmax(const at::Tensor& self, int64_t dim,
                     bool keepdim) const override;
   at::Tensor argmax(const at::Tensor& self) const override;
+  at::Tensor _argmax(const at::Tensor& self, int64_t dim,
+                     bool keepdim) const override;
 
   at::Tensor argmin(const at::Tensor& self, int64_t dim,
                     bool keepdim) const override;
   at::Tensor argmin(const at::Tensor& self) const override;
+  at::Tensor _argmin(const at::Tensor& self, int64_t dim,
+                     bool keepdim) const override;
 
   std::tuple<at::Tensor, at::Tensor, at::Tensor> native_batch_norm_backward(
       const at::Tensor& grad_out, const at::Tensor& input,