diff --git a/integration_tests/src/main/python/cast_test.py b/integration_tests/src/main/python/cast_test.py
index f9bdca6000f..53803a17403 100644
--- a/integration_tests/src/main/python/cast_test.py
+++ b/integration_tests/src/main/python/cast_test.py
@@ -61,6 +61,7 @@ def test_cast_nested(data_gen, to_type):
     assert_gpu_and_cpu_are_equal_collect(
             lambda spark : unary_op_df(spark, data_gen).select(f.col('a').cast(to_type)))
 
+@datagen_overrides(seed=0, reason="https://github.com/NVIDIA/spark-rapids/issues/9781")
 def test_cast_string_date_valid_format():
     # In Spark 3.2.0+ the valid format changed, and we cannot support all of the format.
     # This provides values that are valid in all of those formats.
@@ -259,7 +260,7 @@ def test_cast_long_to_decimal_overflow():
             f.col('a').cast(DecimalType(18, -1))))
 
 # casting these types to string should be passed
-basic_gens_for_cast_to_string = [ByteGen, ShortGen, IntegerGen, LongGen, StringGen, BooleanGen, DateGen, TimestampGen] 
+basic_gens_for_cast_to_string = [ByteGen, ShortGen, IntegerGen, LongGen, StringGen, BooleanGen, DateGen, TimestampGen]
 basic_array_struct_gens_for_cast_to_string = [f() for f in basic_gens_for_cast_to_string] + [null_gen] + decimal_gens
 
 # We currently do not generate the exact string as Spark for some decimal values of zero
@@ -300,7 +301,7 @@ def _assert_cast_to_string_equal (data_gen, conf):
 @pytest.mark.parametrize('legacy', ['true', 'false'])
 def test_cast_array_to_string(data_gen, legacy):
     _assert_cast_to_string_equal(
-        data_gen, 
+        data_gen,
         {"spark.sql.legacy.castComplexTypesToString.enabled": legacy})
 
 
@@ -319,7 +320,7 @@ def test_cast_array_with_unmatched_element_to_string(data_gen, legacy):
 @pytest.mark.parametrize('legacy', ['true', 'false'])
 def test_cast_map_to_string(data_gen, legacy):
     _assert_cast_to_string_equal(
-        data_gen, 
+        data_gen,
         {"spark.sql.legacy.castComplexTypesToString.enabled": legacy})
 
 
@@ -338,7 +339,7 @@ def test_cast_map_with_unmatched_element_to_string(data_gen, legacy):
 @pytest.mark.parametrize('legacy', ['true', 'false'])
 def test_cast_struct_to_string(data_gen, legacy):
     _assert_cast_to_string_equal(
-        data_gen, 
+        data_gen,
         {"spark.sql.legacy.castComplexTypesToString.enabled": legacy}
     )
 
@@ -355,7 +356,7 @@ def was_broken_for_nested_null(spark):
         return df.select(df._1.cast(StringType()))
 
     assert_gpu_and_cpu_are_equal_collect(
-        was_broken_for_nested_null, 
+        was_broken_for_nested_null,
         {"spark.sql.legacy.castComplexTypesToString.enabled": 'true' if cast_conf == 'LEGACY' else 'false'}
     )
 
@@ -372,7 +373,7 @@ def broken_df(spark):
         return df.select(df.a.cast(StringType())).filter(df.b > 1)
 
     assert_gpu_and_cpu_are_equal_collect(
-        broken_df, 
+        broken_df,
         {"spark.sql.legacy.castComplexTypesToString.enabled": 'true' if cast_conf == 'LEGACY' else 'false'}
     )
 
@@ -381,7 +382,7 @@ def broken_df(spark):
 @pytest.mark.xfail(reason='casting this type to string is not an exact match')
 def test_cast_struct_with_unmatched_element_to_string(data_gen, legacy):
     _assert_cast_to_string_equal(
-        data_gen, 
+        data_gen,
         {"spark.rapids.sql.castFloatToString.enabled"       : "true",
          "spark.sql.legacy.castComplexTypesToString.enabled": legacy}
     )
diff --git a/integration_tests/src/main/python/string_test.py b/integration_tests/src/main/python/string_test.py
index 0832621cdf4..65865d0bdc1 100644
--- a/integration_tests/src/main/python/string_test.py
+++ b/integration_tests/src/main/python/string_test.py
@@ -786,6 +786,7 @@ def test_like_complex_escape():
                              pytest.param(10, r'-?[0-9]{1,18}',       id='from_10'),
                              pytest.param(16, r'-?[0-9a-fA-F]{1,15}', id='from_16')
                          ])
+@datagen_overrides(seed=0, reason='https://github.com/NVIDIA/spark-rapids/issues/9784')
 # to_base can be positive and negative
 @pytest.mark.parametrize('to_base', [10, 16], ids=['to_plus10', 'to_plus16'])
 def test_conv_dec_to_from_hex(from_base, to_base, pattern):
@@ -798,10 +799,10 @@ def test_conv_dec_to_from_hex(from_base, to_base, pattern):
         conf={'spark.rapids.sql.expression.Conv': True}
     )
 
-format_number_gens = integral_gens + [DecimalGen(precision=7, scale=7), DecimalGen(precision=18, scale=0), 
-                                      DecimalGen(precision=18, scale=3), DecimalGen(precision=36, scale=5), 
-                                      DecimalGen(precision=36, scale=-5), DecimalGen(precision=38, scale=10), 
-                                      DecimalGen(precision=38, scale=-10), 
+format_number_gens = integral_gens + [DecimalGen(precision=7, scale=7), DecimalGen(precision=18, scale=0),
+                                      DecimalGen(precision=18, scale=3), DecimalGen(precision=36, scale=5),
+                                      DecimalGen(precision=36, scale=-5), DecimalGen(precision=38, scale=10),
+                                      DecimalGen(precision=38, scale=-10),
                                       DecimalGen(precision=38, scale=30, special_cases=[Decimal('0.000125')]),
                                       DecimalGen(precision=38, scale=32, special_cases=[Decimal('0.000125')]),
                                       DecimalGen(precision=38, scale=37, special_cases=[Decimal('0.000125')])]