diff --git a/cupy/_indexing/generate.py b/cupy/_indexing/generate.py
index 3985c4289f7..eaaab361569 100644
--- a/cupy/_indexing/generate.py
+++ b/cupy/_indexing/generate.py
@@ -7,7 +7,6 @@
 import numpy
 
 import cupy
-from cupy import _core
 from cupy._creation import from_data
 from cupy._manipulation import join
 
@@ -40,16 +39,14 @@ def __getitem__(self, key):
         trans1d = self.trans1d
         ndmin = self.ndmin
         objs = []
+        arrays = []
         scalars = []
-        arraytypes = []
-        scalartypes = []
         if isinstance(key, str):
             raise NotImplementedError
         if not isinstance(key, tuple):
             key = (key,)
 
         for i, k in enumerate(key):
-            scalar = False
             if isinstance(k, slice):
                 raise NotImplementedError
             elif isinstance(k, str):
@@ -60,20 +57,17 @@ def __getitem__(self, key):
             elif type(k) in numpy.ScalarType:
                 newobj = from_data.array(k, ndmin=ndmin)
                 scalars.append(i)
-                scalar = True
-                scalartypes.append(newobj.dtype)
             else:
                 newobj = from_data.array(k, copy=False, ndmin=ndmin)
                 if ndmin > 1:
                     ndim = from_data.array(k, copy=False).ndim
                     if trans1d != -1 and ndim < ndmin:
                         newobj = self._output_obj(newobj, ndim, ndmin, trans1d)
+                arrays.append(newobj)
 
             objs.append(newobj)
-            if not scalar and isinstance(newobj, _core.ndarray):
-                arraytypes.append(newobj.dtype)
 
-        final_dtype = numpy.find_common_type(arraytypes, scalartypes)
+        final_dtype = numpy.result_type(*arrays, *scalars)
         if final_dtype is not None:
             for k in scalars:
                 objs[k] = objs[k].astype(final_dtype)
diff --git a/cupyx/scipy/linalg/_special_matrices.py b/cupyx/scipy/linalg/_special_matrices.py
index 2ec70bc9a05..8d9ca364531 100644
--- a/cupyx/scipy/linalg/_special_matrices.py
+++ b/cupyx/scipy/linalg/_special_matrices.py
@@ -294,8 +294,7 @@ def block_diag(*arrs):
 
     shapes = tuple(a.shape for a in arrs)
     shape = tuple(sum(x) for x in zip(*shapes))
-    dtype = cupy.find_common_type([a.dtype for a in arrs], [])
-    out = cupy.zeros(shape, dtype=dtype)
+    out = cupy.zeros(shape, dtype=cupy.result_type(*arrs))
     r, c = 0, 0
     for arr in arrs:
         rr, cc = arr.shape
diff --git a/cupyx/scipy/sparse/_sputils.py b/cupyx/scipy/sparse/_sputils.py
index 1e44acfbc1a..b00d0ab0198 100644
--- a/cupyx/scipy/sparse/_sputils.py
+++ b/cupyx/scipy/sparse/_sputils.py
@@ -109,7 +109,7 @@ def upcast(*args):
     if t is not None:
         return t
 
-    upcast = cupy.find_common_type(args, [])
+    upcast = numpy.result_type(*args)
 
     for t in supported_dtypes:
         if cupy.can_cast(upcast, t):
diff --git a/cupyx/scipy/sparse/linalg/_interface.py b/cupyx/scipy/sparse/linalg/_interface.py
index 64a10403586..7ee35e02654 100644
--- a/cupyx/scipy/sparse/linalg/_interface.py
+++ b/cupyx/scipy/sparse/linalg/_interface.py
@@ -356,7 +356,7 @@ def _get_dtype(operators, dtypes=None):
     for obj in operators:
         if obj is not None and hasattr(obj, 'dtype'):
             dtypes.append(obj.dtype)
-    return cupy.find_common_type(dtypes, [])
+    return cupy.result_type(*dtypes)
 
 
 class _SumLinearOperator(LinearOperator):
diff --git a/tests/cupy_tests/indexing_tests/test_generate.py b/tests/cupy_tests/indexing_tests/test_generate.py
index 5d92f8bbd09..6e3f4cf3f52 100644
--- a/tests/cupy_tests/indexing_tests/test_generate.py
+++ b/tests/cupy_tests/indexing_tests/test_generate.py
@@ -74,7 +74,8 @@ def test_r_8(self, xp, dtype):
         return xp.r_[a, b, c]
 
     @testing.for_all_dtypes()
-    @testing.numpy_cupy_array_equal()
+    @testing.numpy_cupy_array_equal(
+        type_check=(numpy.lib.NumpyVersion(numpy.__version__) >= "1.25.0"))
     def test_r_2(self, xp, dtype):
         a = xp.array([1, 2, 3], dtype)
         return xp.r_[a, 0, 0, a]