diff --git a/pandas/compat/numpy/function.py b/pandas/compat/numpy/function.py
index a36e25a9df410..4df30f7f4a8a7 100644
--- a/pandas/compat/numpy/function.py
+++ b/pandas/compat/numpy/function.py
@@ -138,6 +138,7 @@ def validate_argmax_with_skipna(skipna: bool | ndarray | None, args, kwargs) ->
 ARGSORT_DEFAULTS["kind"] = "quicksort"
 ARGSORT_DEFAULTS["order"] = None
 ARGSORT_DEFAULTS["kind"] = None
+ARGSORT_DEFAULTS["stable"] = None
 
 
 validate_argsort = CompatValidator(
@@ -149,6 +150,7 @@ def validate_argmax_with_skipna(skipna: bool | ndarray | None, args, kwargs) ->
 ARGSORT_DEFAULTS_KIND: dict[str, int | None] = {}
 ARGSORT_DEFAULTS_KIND["axis"] = -1
 ARGSORT_DEFAULTS_KIND["order"] = None
+ARGSORT_DEFAULTS_KIND["stable"] = None
 validate_argsort_kind = CompatValidator(
     ARGSORT_DEFAULTS_KIND, fname="argsort", max_fname_arg_count=0, method="both"
 )
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index 88a08dd55f739..c36dcda6e2972 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -956,7 +956,7 @@ def __array_ufunc__(self, ufunc: np.ufunc, method: str_t, *inputs, **kwargs):
         return self.__array_wrap__(result)
 
     @final
-    def __array_wrap__(self, result, context=None):
+    def __array_wrap__(self, result, context=None, return_scalar=False):
         """
         Gets called after a ufunc and other functions e.g. np.split.
         """
diff --git a/pandas/core/series.py b/pandas/core/series.py
index 83eb545b9b681..f06a1eb533ba4 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -4066,6 +4066,7 @@ def argsort(
         axis: Axis = 0,
         kind: SortKind = "quicksort",
         order: None = None,
+        stable: None = None,
     ) -> Series:
         """
         Return the integer indices that would sort the Series values.
@@ -4082,6 +4083,8 @@ def argsort(
             information. 'mergesort' and 'stable' are the only stable algorithms.
         order : None
             Has no effect but is accepted for compatibility with numpy.
+        stable : None
+            Has no effect but is accepted for compatibility with numpy.
 
         Returns
         -------