diff --git a/ttnn/cpp/ttnn/operations/eltwise/binary/binary_pybind.hpp b/ttnn/cpp/ttnn/operations/eltwise/binary/binary_pybind.hpp
index 8c6bb9291a6..919b624b39b 100644
--- a/ttnn/cpp/ttnn/operations/eltwise/binary/binary_pybind.hpp
+++ b/ttnn/cpp/ttnn/operations/eltwise/binary/binary_pybind.hpp
@@ -626,13 +626,13 @@ void bind_inplace_operation(py::module& module, const binary_operation_t& operat
 }
 
 template <typename binary_operation_t>
-void bind_logical_inplace_operation(py::module& module, const binary_operation_t& operation, const std::string& description, const std::string& note=" ") {
+void bind_logical_inplace_operation(py::module& module, const binary_operation_t& operation, const std::string& description, const std::string& math, const std::string& note=" ") {
     auto doc = fmt::format(
         R"doc(
         {2}
 
         .. math::
-            \mathrm{{output\_tensor}} = \verb|{0}|(\mathrm{{input\_tensor\_a,input\_tensor\_b}}).
+            {3}
 
         Args:
             input_tensor_a (ttnn.Tensor): the input tensor.
@@ -642,7 +642,7 @@ void bind_logical_inplace_operation(py::module& module, const binary_operation_t
             List of ttnn.Tensor: the output tensor.
 
         Note:
-            {3}
+            {4}
 
         Example:
             >>> tensor1 = ttnn.from_torch(torch.tensor((1, 2), dtype=torch.bfloat16), device=device)
@@ -652,6 +652,7 @@ void bind_logical_inplace_operation(py::module& module, const binary_operation_t
         operation.base_name(),
         operation.python_fully_qualified_name(),
         description,
+        math,
         note);
 
     bind_registered_operation(
@@ -980,9 +981,7 @@ void py_module(py::module& module) {
         module,
         ttnn::logical_xor,
         R"doc(Compute logical_xor :attr:`input_tensor_a` and :attr:`input_tensor_b` and returns the tensor with the same layout as :attr:`input_tensor_a`)doc",
-        R"doc(\mathrm{output\_tensor}_i = (\mathrm{input\_tensor\_a}_i \land \lnot \mathrm{input\_tensor\_b}_i) \lor (\lnot \mathrm{input\_tensor\_a}_i \land \mathrm{input\_tensor\_b}_i)
-        )doc",
-
+        R"doc(\mathrm{output\_tensor}_i = (\mathrm{input\_tensor\_a}_i \land \lnot \mathrm{input\_tensor\_b}_i) \lor (\lnot \mathrm{input\_tensor\_a}_i \land \mathrm{input\_tensor\_b}_i))doc",".",
         R"doc(Supported dtypes, layouts, and ranks:
 
            +----------------------------+---------------------------------+-------------------+
@@ -996,6 +995,7 @@ void py_module(py::module& module) {
         module,
         ttnn::logical_or_,
         R"doc(Compute inplace logical OR of :attr:`input_tensor_a` and :attr:`input_tensor_b` and returns the tensor with the same layout as :attr:`input_tensor_a`)doc",
+        R"doc((\mathrm{{input\_tensor\_a}}_i | \mathrm{{input\_tensor\_b}}_i))doc",
 
         R"doc(Supported dtypes, layouts, and ranks:
 
@@ -1010,6 +1010,7 @@ void py_module(py::module& module) {
         module,
         ttnn::logical_xor_,
         R"doc(Compute inplace logical XOR of :attr:`input_tensor_a` and :attr:`input_tensor_b` and returns the tensor with the same layout as :attr:`input_tensor_a`)doc",
+        R"doc((\mathrm{input\_tensor\_a}_i \land \lnot \mathrm{input\_tensor\_b}_i) \lor (\lnot \mathrm{input\_tensor\_a}_i \land \mathrm{input\_tensor\_b}_i))doc",
 
         R"doc(Supported dtypes, layouts, and ranks:
 
@@ -1024,6 +1025,7 @@ void py_module(py::module& module) {
         module,
         ttnn::logical_and_,
         R"doc(Compute inplace logical AND of :attr:`input_tensor_a` and :attr:`input_tensor_b` and returns the tensor with the same layout as :attr:`input_tensor_a`)doc",
+        R"doc((\mathrm{{input\_tensor\_a}}_i \& \mathrm{{input\_tensor\_b}}_i))doc",
 
         R"doc(Supported dtypes, layouts, and ranks:
 
diff --git a/ttnn/cpp/ttnn/operations/eltwise/binary/device/binary_composite_op.cpp b/ttnn/cpp/ttnn/operations/eltwise/binary/device/binary_composite_op.cpp
index c0a516b34cb..ef74e088e1a 100644
--- a/ttnn/cpp/ttnn/operations/eltwise/binary/device/binary_composite_op.cpp
+++ b/ttnn/cpp/ttnn/operations/eltwise/binary/device/binary_composite_op.cpp
@@ -151,13 +151,6 @@ Tensor _atan2(const Tensor& input_a, const Tensor& input_b, const std::optional<
     return res;
 }
 
-// Tensor _logical_xor(const Tensor& input_a, const Tensor& input_b, const std::optional<MemoryConfig>& output_mem_config) {
-//     Tensor in_a_eq_zero = ttnn::eqz(input_a, output_mem_config);
-//     Tensor in_b_eq_zero = ttnn::eqz(input_b, output_mem_config);
-//     Tensor in_b_neq_zero = ttnn::nez(input_b, output_mem_config);
-//     Tensor result = ttnn::where(in_a_eq_zero, in_b_neq_zero, in_b_eq_zero);
-//     return result;
-//}
 
 Tensor ExecuteDiv::invoke(uint8_t queue_id, const Tensor& input, float value, bool accurate_mode, const std::string& round_mode, const std::optional<MemoryConfig>& output_mem_config, std::optional<Tensor> output_tensor) {
     TT_FATAL((round_mode == "None" || round_mode == "trunc" || round_mode == "floor"), "Incorrect rounding mode (expected 'None', 'trunc', or 'floor')");
@@ -324,13 +317,6 @@ Tensor _floor_div(const Tensor& input_a, const Tensor& input_b, const std::optio
         result);
 }
 
-// Tensor _logical_xor_(const Tensor& input_a, const Tensor& input_b, const std::optional<MemoryConfig>& output_mem_config) {
-//     Tensor in_a_eq_zero = ttnn::eqz(input_a, output_mem_config, input_a );
-//     Tensor in_b_eq_zero = ttnn::nez(input_b, output_mem_config, input_b );
-//     in_b_eq_zero = ttnn::eqz(input_b, output_mem_config);
-//     Tensor result = ttnn::where(input_a, input_b, in_b_eq_zero, output_mem_config, input_a);
-//     return result;
-// }
 
 Tensor _scatter(const Tensor& input_a, const Tensor& input_b, const std::optional<MemoryConfig>& output_mem_config) {
     tt::tt_metal::Array4D start_index = {0, 0, 0, 0};