diff --git a/test/xpu/skip_list_common.py b/test/xpu/skip_list_common.py
index 5e70eebf4..6f8367e58 100644
--- a/test/xpu/skip_list_common.py
+++ b/test/xpu/skip_list_common.py
@@ -24,6 +24,7 @@
         # This case is marked as skip but XPU failed. However, CUDA and XPU throw the same runtime error.
         "test_out_histc_xpu_float32",
         # Data type is not supported in oneDNN!
+        # https://github.com/intel/torch-xpu-ops/issues/1896
         "test_dtypes_nn_functional_conv1d_xpu",
         "test_dtypes_nn_functional_conv2d_xpu",
         "test_dtypes_nn_functional_conv3d_xpu",
@@ -99,7 +100,6 @@
         # unexpected success because of cpu fallback
         # Linalg OPs not supported
         "test_out_triangular_solve_xpu_float32",
-        # Newly added:
         # Cuda skipped it
         "test_non_standard_bool_values_sort_xpu_bool",  # The implementation aligns with CUDA, RuntimeError: "sort" not implemented for 'Bool'.
         # Cuda XFAIL (stock pytorch commit: e7cf7d0)
@@ -1414,8 +1414,7 @@
         "test_gemm_bias_tunableop_xpu_bfloat16",
         "test_scaled_gemm_tunableop_xpu_float8_e4m3fnuz",
         "test_scaled_gemm_tunableop_xpu_float8_e5m2fnuz",
-        # CUDA bias cases added in latest PyTorch
-        # AttributeError: module 'torch._C' has no attribute '_cuda_tunableop_enable'
+        # https://github.com/intel/torch-xpu-ops/issues/2066
         "test_matmul_check_entries_tunableop_xpu_float16",
         "test_minimum_tuning_iteration_tunableop_xpu_float16",
         "test_validator_tunableop_rocm_xpu_float32",
@@ -2968,8 +2967,6 @@
         "test_meta_outplace_vdot_xpu_complex",
         # Unexpected success:
         "test_dispatch_symbolic_meta_outplace_all_strides_narrow_copy_xpu_float32",
-        # New added case in 2.7
-        "test_nonzero_xpu",
         # https://github.com/intel/torch-xpu-ops/issues/1569
         # RuntimeError: output 0: meta disagrees with real impl
         "test_dispatch_meta_outplace_norm_fro_xpu_bfloat16",