diff --git a/backends/arm/test/misc/test_const_shape.py b/backends/arm/test/misc/test_const_shape.py
index 5e3d1233b73..c971682911b 100644
--- a/backends/arm/test/misc/test_const_shape.py
+++ b/backends/arm/test/misc/test_const_shape.py
@@ -35,7 +35,7 @@ def call_operator(self, op, args, kwargs, meta, updated: bool | None = False):
             return super().call_operator(op, args, kwargs, meta, updated)
 
 
-def test_const_shape_injects_meta_no_target():
+def test_const_shape_injects_meta():
     class M(torch.nn.Module):
         def forward(self, x):
             return x + 1
diff --git a/backends/arm/test/misc/test_count_tosa_ops.py b/backends/arm/test/misc/test_count_tosa_ops.py
index 2f13f1f05f6..127a4623b36 100644
--- a/backends/arm/test/misc/test_count_tosa_ops.py
+++ b/backends/arm/test/misc/test_count_tosa_ops.py
@@ -14,7 +14,7 @@ def forward(self, x, y):
         return x + y
 
 
-def test_count_tosa_ops_add_no_target():
+def test_count_tosa_ops_add():
     model = AddModule()
     test_data = (torch.randn(1, 8, 8, 8), torch.randn(1, 8, 8, 8))
     pipeline = TosaPipelineFP[type(test_data)](
@@ -27,7 +27,7 @@ def test_count_tosa_ops_add_no_target():
     pipeline.run()
 
 
-def test_count_tosa_ops_2_adds_no_target():
+def test_count_tosa_ops_2_adds():
     model = AddModule()
     test_data = (torch.randn(1, 8, 8, 8), torch.randn(1, 8, 8, 8))
     pipeline = TosaPipelineFP[type(test_data)](
diff --git a/backends/arm/test/misc/test_debug_hook.py b/backends/arm/test/misc/test_debug_hook.py
index 2dfe1307718..92227f7c3cc 100644
--- a/backends/arm/test/misc/test_debug_hook.py
+++ b/backends/arm/test/misc/test_debug_hook.py
@@ -1,4 +1,4 @@
-# Copyright 2025 Arm Limited and/or its affiliates.
+# Copyright 2025-2026 Arm Limited and/or its affiliates.
 #
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
@@ -160,7 +160,7 @@ def _compare_node_and_schema(debug_event: DebugSchema, mocked_node):
 
 
 @common.parametrize("test_data", TESTCASES)
-def test_debug_hook_add_json_no_target(test_data: DebugHookTestCase):
+def test_debug_hook_add_json(test_data: DebugHookTestCase):
     hook = DebugHook(ArmCompileSpec.DebugMode.JSON)
     hook.add(cast(Node, test_data.mock_node), test_data.tosa_op, test_data.op_id)
 
@@ -173,7 +173,7 @@ def test_debug_hook_add_json_no_target(test_data: DebugHookTestCase):
 
 
 @common.parametrize("test_data", TESTCASES)
-def test_debug_hook_add_tosa_no_target(test_data: DebugHookTestCase):
+def test_debug_hook_add_tosa(test_data: DebugHookTestCase):
     hook = DebugHook(ArmCompileSpec.DebugMode.TOSA)
     hook.add(cast(Node, test_data.mock_node), test_data.tosa_op, test_data.op_id)
 
diff --git a/backends/arm/test/misc/test_mixed_fp_bf16_partition.py b/backends/arm/test/misc/test_mixed_fp_bf16_partition.py
index 7385cd4863c..7851849a7a3 100644
--- a/backends/arm/test/misc/test_mixed_fp_bf16_partition.py
+++ b/backends/arm/test/misc/test_mixed_fp_bf16_partition.py
@@ -50,7 +50,7 @@ def forward(
         return self.conv_bf16(x), self.conv_fp32(y)
 
 
-def test_mixed_fp32_bf16_inputs_rejected_no_target():
+def test_mixed_fp32_bf16_inputs_rejected():
     test_data = (torch.randn(1, 3, 8, 8, dtype=torch.float32),)
     exported_program = to_edge(
         export(MixedConv(torch.bfloat16), test_data, strict=True),
@@ -68,7 +68,7 @@ def test_mixed_fp32_bf16_inputs_rejected_no_target():
     assert "Mixed floating-point input" in reporter.get_table_report()
 
 
-def test_mixed_bf16_cast_fp32_inputs_accepted_no_target():
+def test_mixed_bf16_cast_fp32_inputs_accepted():
     test_data = (torch.randn(1, 3, 8, 8, dtype=torch.float32),)
     exported_program = to_edge(
         export(CastInputConv(torch.bfloat16), test_data, strict=True)
@@ -84,7 +84,7 @@ def test_mixed_bf16_cast_fp32_inputs_accepted_no_target():
     assert support.is_node_supported(exported_program.graph_module, conv_node) is True
 
 
-def test_bf16_rejected_without_tosa_support_no_target():
+def test_bf16_rejected_without_tosa_support():
     test_data = (torch.randn(1, 3, 8, 8, dtype=torch.bfloat16),)
     exported_program = to_edge(
         export(MixedConv(torch.bfloat16), test_data, strict=True)
@@ -101,7 +101,7 @@ def test_bf16_rejected_without_tosa_support_no_target():
     assert "Had torch.bfloat16 input" in reporter.get_table_report()
 
 
-def test_parallel_bf16_fp32_inputs_accepted_no_target():
+def test_parallel_bf16_fp32_inputs_accepted():
     test_data = (
         torch.randn(1, 3, 8, 8, dtype=torch.bfloat16),
         torch.randn(1, 3, 8, 8, dtype=torch.float32),
diff --git a/backends/arm/test/misc/test_model_evaluator.py b/backends/arm/test/misc/test_model_evaluator.py
index b5b1cb3b118..36c98670e0c 100644
--- a/backends/arm/test/misc/test_model_evaluator.py
+++ b/backends/arm/test/misc/test_model_evaluator.py
@@ -27,7 +27,7 @@ def mocked_model_2(input: torch.Tensor) -> torch.Tensor:
 class TestModelEvaluator(unittest.TestCase):
     """Tests the Arm model evaluators."""
 
-    def test_get_model_error_no_target(self):
+    def test_get_model_error(self):
         example_input = torch.tensor([[1.0, 2.0, 3.0, 4.0]])
         evaluator = NumericalModelEvaluator(
             "dummy_model",
@@ -44,7 +44,7 @@ def test_get_model_error_no_target(self):
         self.assertEqual(metrics["max_percentage_error"], 25.0)
         self.assertEqual(metrics["mean_absolute_error"], 0.25)
 
-    def test_get_compression_ratio_no_target(self):
+    def test_get_compression_ratio(self):
         with tempfile.NamedTemporaryFile(delete=True) as temp_bin:
             torch.save(COMPRESSION_RATIO_TEST, temp_bin)
 
diff --git a/backends/arm/test/misc/test_pass_pipeline_config.py b/backends/arm/test/misc/test_pass_pipeline_config.py
index d017d27ebc4..84575fb04fa 100644
--- a/backends/arm/test/misc/test_pass_pipeline_config.py
+++ b/backends/arm/test/misc/test_pass_pipeline_config.py
@@ -17,7 +17,7 @@
 from executorch.backends.arm.tosa.specification import TosaSpecification
 
 
-def test_pipeline_config_override_outside_compile_spec_no_target():
+def test_pipeline_config_override_outside_compile_spec():
     compile_spec = TosaCompileSpec(
         TosaSpecification.create_from_string("TOSA-1.00+INT")
     )
diff --git a/backends/arm/test/misc/test_post_quant_device_switch.py b/backends/arm/test/misc/test_post_quant_device_switch.py
index 064a6d16d29..8d4ff95dbc8 100644
--- a/backends/arm/test/misc/test_post_quant_device_switch.py
+++ b/backends/arm/test/misc/test_post_quant_device_switch.py
@@ -196,7 +196,7 @@ def _to_meta_inputs(
 
 
 @pytest.mark.parametrize("case", _TEST_CASES, ids=[case.name for case in _TEST_CASES])
-def test_post_quant_device_switch_no_target(case: MetaRetraceCase) -> None:
+def test_post_quant_device_switch(case: MetaRetraceCase) -> None:
     """This test tests that moving a model to another device after quantiation
     works.
     """
diff --git a/backends/arm/test/misc/test_public_api_manifest.py b/backends/arm/test/misc/test_public_api_manifest.py
index b7711c361e7..e891584364b 100644
--- a/backends/arm/test/misc/test_public_api_manifest.py
+++ b/backends/arm/test/misc/test_public_api_manifest.py
@@ -30,7 +30,7 @@ def _entry_block(path: str, entry: dict[str, str]) -> str:
     )
 
 
-def test_public_api_manifest_entries_are_well_formed_no_target():
+def test_public_api_manifest_entries_are_well_formed():
     entries = _collect_public_api()
 
     assert entries
@@ -46,7 +46,7 @@ def test_public_api_manifest_entries_are_well_formed_no_target():
             assert path.rsplit(".", 1)[0] in entries
 
 
-def test_public_api_manifest_matches_generator_no_target():
+def test_public_api_manifest_matches_generator():
     entries = _collect_public_api()
     manifest = _render_manifest(entries)
 
@@ -60,7 +60,7 @@ def test_public_api_manifest_matches_generator_no_target():
     assert manifest == Path(RUNNING_MANIFEST_PATH).read_text(encoding="utf-8")
 
 
-def test_public_api_manifest_collection_handles_deprecated_symbols_no_target():
+def test_public_api_manifest_collection_handles_deprecated_symbols():
     @deprecated("old foo")
     def old_foo(x: int) -> int:
         return x
@@ -73,7 +73,7 @@ def old_foo(x: int) -> int:
     assert "old_foo" not in entries
 
 
-def test_public_api_manifest_collection_excludes_init_for_equivalent_classes_no_target():
+def test_public_api_manifest_collection_excludes_init_for_equivalent_classes():
     class ExplicitInit:
         def __init__(self, x: int = 0) -> None:
             del x
diff --git a/backends/arm/test/misc/test_runner_utils.py b/backends/arm/test/misc/test_runner_utils.py
index 240013594bc..10a8b6df3a6 100644
--- a/backends/arm/test/misc/test_runner_utils.py
+++ b/backends/arm/test/misc/test_runner_utils.py
@@ -17,7 +17,7 @@ def exported_program(self):
         return object()
 
 
-def test_run_corstone_no_target_uses_short_input_aliases_in_semihosting_cmd(
+def test_run_corstone_uses_short_input_aliases_in_semihosting_cmd(
     monkeypatch, tmp_path: Path
 ) -> None:
     long_input_paths = [
diff --git a/backends/arm/test/misc/test_shared_qspecs.py b/backends/arm/test/misc/test_shared_qspecs.py
index 343ce99edde..de07bd5f6c2 100644
--- a/backends/arm/test/misc/test_shared_qspecs.py
+++ b/backends/arm/test/misc/test_shared_qspecs.py
@@ -622,7 +622,7 @@ def forward(self, x):
 
 
 @parametrize("test_case", test_cases)
-def test_shared_qspec_quantizer_no_target(test_case):
+def test_shared_qspec_quantizer(test_case):
     """Test that ops which does not change dynamic range are able to use int8
     portable kernels.
     """
@@ -655,7 +655,7 @@ def test_shared_qspec_quantizer_no_target(test_case):
 
 
 @parametrize("test_case", float_test_cases)
-def test_shared_qspec_quantizer_no_qspecs_no_target(test_case):
+def test_shared_qspec_quantizer_no_qspecs(test_case):
     """Test that ops which does not change dynamic range are able to use int8
     portable kernels.
     """
@@ -671,7 +671,7 @@ def test_shared_qspec_quantizer_no_qspecs_no_target(test_case):
     _check_quant_params(pipeline, test_case.model.quant_params)
 
 
-def test_maximum_mixed_int8_int16_inputs_no_target():
+def test_maximum_mixed_int8_int16_inputs():
     model = MixedMaximumInt8Int16()
     inputs = (ramp_tensor(-2, 2, (2, 3, 4)),)
 
diff --git a/backends/arm/test/misc/test_tosa_dialect_shape_ops.py b/backends/arm/test/misc/test_tosa_dialect_shape_ops.py
index a5de5de648d..c4acdd98bf0 100644
--- a/backends/arm/test/misc/test_tosa_dialect_shape_ops.py
+++ b/backends/arm/test/misc/test_tosa_dialect_shape_ops.py
@@ -41,7 +41,7 @@ def _expr_equals(sym: torch.SymInt, expected: sympy.Expr) -> bool:
 
 
 # Test that DIM can extract a symbolic dimension from a tensor when the TOSA specification supports the shape extension.
-def test_dim_extracts_symbolic_dimension_no_target():
+def test_dim_extracts_symbolic_dimension():
     shape_env = ShapeEnv()
     s0 = _make_symint(shape_env, "s0", hint=4)
 
@@ -59,7 +59,7 @@ def test_dim_extracts_symbolic_dimension_no_target():
 
 # Test that DIM raises an error when the TOSA specification doesn't support the shape extension, as DIM relies on shape
 # expressions to return symbolic dimensions.
-def test_dim_requires_shape_extension_no_target():
+def test_dim_requires_shape_extension():
     spec_no_shape = TosaSpecification.create_from_string("TOSA-1.0+FP")
     shape_env = ShapeEnv()
     s0 = _make_symint(shape_env, "s0", hint=3)
@@ -74,7 +74,7 @@ def test_dim_requires_shape_extension_no_target():
 
 
 # Test that CONST_SHAPE creates a constant shape tensor and returns the expected shape list.
-def test_const_shape_no_target():
+def test_const_shape():
     with TosaLoweringContext(
         TosaSpecification.create_from_string("TOSA-1.1+FP+shape")
     ), FakeTensorMode():
@@ -83,7 +83,7 @@ def test_const_shape_no_target():
 
 
 # Test that CONCAT_SHAPE with constant shapes performs concatenation and returns a constant shape.
-def test_concat_const_shapes_no_target():
+def test_concat_const_shapes():
     with TosaLoweringContext(
         TosaSpecification.create_from_string("TOSA-1.1+FP+shape")
     ), FakeTensorMode():
@@ -96,7 +96,7 @@ def test_concat_const_shapes_no_target():
 
 
 # Test that CONCAT_SHAPE with symbolic shapes produces a symbolic expression concatenating the dimensions.
-def test_concat_symbolic_shape_no_target():
+def test_concat_symbolic_shape():
     shape_env = ShapeEnv()
     s0 = _make_symint(shape_env, "s0", hint=2)
     s1 = _make_symint(shape_env, "s1", hint=3)
@@ -116,7 +116,7 @@ def test_concat_symbolic_shape_no_target():
     assert _expr(result[1]) == "s1"
 
 
-def test_concat_mixed_shape_no_target():
+def test_concat_mixed_shape():
     shape_env = ShapeEnv()
     s0 = _make_symint(shape_env, "s0", hint=2)
 
@@ -136,7 +136,7 @@ def test_concat_mixed_shape_no_target():
 
 # Test that CONCAT_SHAPE raises an error when given fewer than 2 shape tensors, as it requires at least 2 to
 # concatenate.
-def test_concat_shape_requires_arguments_no_target():
+def test_concat_shape_requires_arguments():
     with pytest.raises(
         TosaValueError, match="CONCAT_SHAPE expected 2 or more shape tensors"
     ):
@@ -147,7 +147,7 @@ def test_concat_shape_requires_arguments_no_target():
 
 
 # Test ADD_SHAPE with constant values, which should perform elementwise addition and return a constant shape.
-def test_add_const_shape_no_target():
+def test_add_const_shape():
     shape_env = ShapeEnv()
     with TosaLoweringContext(
         TosaSpecification.create_from_string("TOSA-1.1+FP+shape"), shape_env
@@ -160,7 +160,7 @@ def test_add_const_shape_no_target():
 
 
 # Test ADD_SHAPE with symbolic values, which should produce a symbolic expression adding the two dimensions.
-def test_add_symbolic_shape_no_target():
+def test_add_symbolic_shape():
     shape_env = ShapeEnv()
     s0 = _make_symint(shape_env, "s0", hint=2)
     s1 = _make_symint(shape_env, "s1", hint=3)
@@ -179,7 +179,7 @@ def test_add_symbolic_shape_no_target():
     assert _expr_equals(result[0], sympy.Symbol("s0") + sympy.Symbol("s1"))
 
 
-def test_add_mixed_shape_no_target():
+def test_add_mixed_shape():
     shape_env = ShapeEnv()
     s0 = _make_symint(shape_env, "s0", hint=2)
 
@@ -197,7 +197,7 @@ def test_add_mixed_shape_no_target():
 
 
 # Test SUB_SHAPE with constant values, which should perform subtraction and return a constant shape.
-def test_sub_const_shape_no_target():
+def test_sub_const_shape():
     shape_env = ShapeEnv()
     with TosaLoweringContext(
         TosaSpecification.create_from_string("TOSA-1.1+FP+shape"), shape_env
@@ -210,7 +210,7 @@ def test_sub_const_shape_no_target():
 
 
 # Test SUB_SHAPE with symbolic values, which should produce a Sub expression.
-def test_sub_symbolic_shape_no_target():
+def test_sub_symbolic_shape():
     shape_env = ShapeEnv()
     s0 = _make_symint(shape_env, "s0", hint=2)
     s1 = _make_symint(shape_env, "s1", hint=3)
@@ -230,7 +230,7 @@ def test_sub_symbolic_shape_no_target():
     assert _expr_equals(result[0], sympy.Symbol("s0") - sympy.Symbol("s1"))
 
 
-def test_sub_mixed_shape_no_target():
+def test_sub_mixed_shape():
     shape_env = ShapeEnv()
     s0 = _make_symint(shape_env, "s0", hint=3)
 
@@ -249,7 +249,7 @@ def test_sub_mixed_shape_no_target():
 
 
 # Test MUL_SHAPE with constant values, which should perform multiplication and return a constant shape.
-def test_mul_const_shape_no_target():
+def test_mul_const_shape():
     shape_env = ShapeEnv()
     with TosaLoweringContext(
         TosaSpecification.create_from_string("TOSA-1.1+FP+shape"), shape_env
@@ -262,7 +262,7 @@ def test_mul_const_shape_no_target():
 
 
 # Test MUL_SHAPE with symbolic values, which should produce a Mul expression.
-def test_mul_symbolic_shape_no_target():
+def test_mul_symbolic_shape():
     shape_env = ShapeEnv()
     s0 = _make_symint(shape_env, "s0", hint=2)
     s1 = _make_symint(shape_env, "s1", hint=3)
@@ -281,7 +281,7 @@ def test_mul_symbolic_shape_no_target():
     assert _expr_equals(result[0], sympy.Symbol("s0") * sympy.Symbol("s1"))
 
 
-def test_mul_mixed_shape_no_target():
+def test_mul_mixed_shape():
     shape_env = ShapeEnv()
     s0 = _make_symint(shape_env, "s0", hint=4)
 
@@ -299,7 +299,7 @@ def test_mul_mixed_shape_no_target():
 
 
 # Test DIV_FLOOR_SHAPE with constant values, which should perform floor division and return a constant shape.
-def test_div_floor_const_shape_no_target():
+def test_div_floor_const_shape():
     shape_env = ShapeEnv()
     with TosaLoweringContext(
         TosaSpecification.create_from_string("TOSA-1.1+FP+shape"), shape_env
@@ -312,7 +312,7 @@ def test_div_floor_const_shape_no_target():
 
 
 # Test DIV_FLOOR_SHAPE with symbolic values, which should produce a FloorDiv expression.
-def test_div_floor_symbolic_shape_no_target():
+def test_div_floor_symbolic_shape():
     shape_env = ShapeEnv()
     s0 = _make_symint(shape_env, "s0", hint=8)
     s1 = _make_symint(shape_env, "s1", hint=3)
@@ -330,7 +330,7 @@ def test_div_floor_symbolic_shape_no_target():
     assert _expr_equals(result[0], sympy.sympify("(s0//s1)"))
 
 
-def test_div_floor_mixed_shape_no_target():
+def test_div_floor_mixed_shape():
     shape_env = ShapeEnv()
     s0 = _make_symint(shape_env, "s0", hint=4)
 
diff --git a/backends/arm/test/misc/test_tosa_spec.py b/backends/arm/test/misc/test_tosa_spec.py
index 7170c7ed4d1..b664d7d63f2 100644
--- a/backends/arm/test/misc/test_tosa_spec.py
+++ b/backends/arm/test/misc/test_tosa_spec.py
@@ -74,7 +74,7 @@ class TestTosaSpecification(unittest.TestCase):
     """Tests the TOSA specification class."""
 
     @parameterized.expand(test_valid_strings)  # type: ignore[misc]
-    def test_version_string_no_target(self, version_string: str, expected_type):
+    def test_version_string(self, version_string: str, expected_type):
         tosa_spec = TosaSpecification.create_from_string(version_string)
         assert isinstance(tosa_spec, expected_type)
         assert [profile in ["INT", "FP"] for profile in tosa_spec.profiles].count(
@@ -90,7 +90,7 @@ def test_version_string_no_target(self, version_string: str, expected_type):
         assert set(tosa_spec.extensions).issubset(allowed_extensions)
 
     @parameterized.expand(test_invalid_strings)  # type: ignore[misc]
-    def test_invalid_version_strings_no_target(self, version_string: str):
+    def test_invalid_version_strings(self, version_string: str):
         tosa_spec = None
         with self.assertRaises(ValueError):
             tosa_spec = TosaSpecification.create_from_string(version_string)
@@ -98,14 +98,12 @@ def test_invalid_version_strings_no_target(self, version_string: str):
         assert tosa_spec is None
 
     @parameterized.expand(test_valid_strings)
-    def test_correct_string_representation_no_target(
-        self, version_string: str, expected_type
-    ):
+    def test_correct_string_representation(self, version_string: str, expected_type):
         tosa_spec = TosaSpecification.create_from_string(version_string)
         assert isinstance(tosa_spec, expected_type)
         assert f"{tosa_spec}" == version_string
 
-    def test_supports_new_1_1_extensions_no_target(self):
+    def test_supports_new_1_1_extensions(self):
         fp_spec = TosaSpecification.create_from_string(
             "TOSA-1.1+FP+shape+int64+random+mxfp+blockscale_ue5m3"
         )
@@ -127,7 +125,7 @@ def test_supports_new_1_1_extensions_no_target(self):
 class TestTosaSpecMapping(unittest.TestCase):
     """Tests the TosaSpecMapping class."""
 
-    def test_mapping_no_target(self):
+    def test_mapping(self):
         mapping = TosaSpecMapping()
         mapping.add(TosaSpecification.create_from_string("TOSA-1.0+INT"), "A")
         # check that the mapping is correct
@@ -136,7 +134,7 @@ def test_mapping_no_target(self):
         assert vals == ["A"]
         assert len(vals) == 1
 
-    def test_mapping_multiple_no_target(self):
+    def test_mapping_multiple(self):
         mapping = TosaSpecMapping()
         mapping.add(TosaSpecification.create_from_string("TOSA-1.0+INT"), "A")
         mapping.add(TosaSpecification.create_from_string("TOSA-1.0+INT"), "B")
@@ -146,7 +144,7 @@ def test_mapping_multiple_no_target(self):
         assert vals == ["A", "B"]
         assert len(vals) == 2
 
-    def test_mapping_different_profiles_no_target(self):
+    def test_mapping_different_profiles(self):
         mapping = TosaSpecMapping()
         mapping.add(TosaSpecification.create_from_string("TOSA-1.0+INT"), "A")
         mapping.add(TosaSpecification.create_from_string("TOSA-1.0+FP"), "B")
@@ -159,7 +157,7 @@ def test_mapping_different_profiles_no_target(self):
         assert len(vals_int) == 1
         assert len(vals_fp) == 1
 
-    def test_mapping_1_1_profiles_no_target(self):
+    def test_mapping_1_1_profiles(self):
         mapping = TosaSpecMapping()
         mapping.add(TosaSpecification.create_from_string("TOSA-1.1+INT"), "A")
         vals = mapping.get(TosaSpecification.create_from_string("TOSA-1.1+INT"))
@@ -167,7 +165,7 @@ def test_mapping_1_1_profiles_no_target(self):
         assert vals == ["A"]
         assert len(vals) == 1
 
-    def test_mapping_different_profiles_combined_consumer_no_target(self):
+    def test_mapping_different_profiles_combined_consumer(self):
         mapping = TosaSpecMapping()
         mapping.add(TosaSpecification.create_from_string("TOSA-1.0+INT"), "A")
         mapping.add(TosaSpecification.create_from_string("TOSA-1.0+FP"), "B")
@@ -180,18 +178,18 @@ def test_mapping_different_profiles_combined_consumer_no_target(self):
         assert "B" in combined_vals
         assert len(combined_vals) == 2
 
-    def test_mapping_no_spec_no_target(self):
+    def test_mapping_no_spec(self):
         mapping = TosaSpecMapping()
         with self.assertRaises(KeyError):
             mapping.get(TosaSpecification.create_from_string("TOSA-1.0+INT"))
 
-    def test_mapping_no_values_for_spec_no_target(self):
+    def test_mapping_no_values_for_spec(self):
         mapping = TosaSpecMapping()
         mapping.add(TosaSpecification.create_from_string("TOSA-1.0+FP"), "A")
         with self.assertRaises(KeyError):
             mapping.get(TosaSpecification.create_from_string("TOSA-1.0+INT"))
 
-    def test_spec_with_different_profiles_no_target(self):
+    def test_spec_with_different_profiles(self):
         mapping = TosaSpecMapping()
         mapping.add(TosaSpecification.create_from_string("TOSA-1.0+FP"), "A")
         mapping.add(TosaSpecification.create_from_string("TOSA-1.0+INT"), "B")
@@ -208,20 +206,20 @@ def test_spec_with_different_profiles_no_target(self):
         assert len(vals_fp) == 1
         assert len(vals_int_fp) == 2
 
-    def test_combined_profiles_no_target(self):
+    def test_combined_profiles(self):
         mapping = TosaSpecMapping()
         with self.assertRaises(ValueError):
             # Don't allow multiple profiles in a single spec
             mapping.add(TosaSpecification.create_from_string("TOSA-1.0+INT+FP"), "A")
 
-    def test_spec_add_with_extension_no_target(self):
+    def test_spec_add_with_extension(self):
         mapping = TosaSpecMapping()
         with self.assertRaises(ValueError):
             mapping.add(
                 TosaSpecification.create_from_string("TOSA-1.0.0+INT+int16"), "A"
             )
 
-    def test_spec_non_canonical_key_no_target(self):
+    def test_spec_non_canonical_key(self):
         mapping = TosaSpecMapping()
         mapping.add(TosaSpecification.create_from_string("TOSA-1.0+INT"), "A")
 
diff --git a/backends/arm/test/passes/test_decompose_einsum_pass.py b/backends/arm/test/passes/test_decompose_einsum_pass.py
index 78c91c7f92d..3e2f2b92d55 100644
--- a/backends/arm/test/passes/test_decompose_einsum_pass.py
+++ b/backends/arm/test/passes/test_decompose_einsum_pass.py
@@ -34,7 +34,7 @@ def _get_int8_quantizer() -> TOSAQuantizer:
     return quantizer
 
 
-def test_decompose_einsum_no_target_rewrites_export_graph() -> None:
+def test_decompose_einsum_rewrites_export_graph() -> None:
     module = EinsumPermuteModule().eval()
     exported_program = export(module, module.get_inputs())
 
diff --git a/backends/arm/test/passes/test_decompose_int16_activation_conv_pass.py b/backends/arm/test/passes/test_decompose_int16_activation_conv_pass.py
index dd3f742cf84..725e0ade760 100644
--- a/backends/arm/test/passes/test_decompose_int16_activation_conv_pass.py
+++ b/backends/arm/test/passes/test_decompose_int16_activation_conv_pass.py
@@ -106,7 +106,7 @@ def forward(self, x: torch.Tensor) -> torch.Tensor:
         return x
 
 
-def test_decompose_conv_with_int16_activation_no_target_fp32_no_decomposition() -> None:
+def test_decompose_conv_with_int16_activation_fp32_no_decomposition() -> None:
     """Test that DecomposeConvWithInt16ActivationPass does NOT decompose
     convolution when using FP32 (no quantization).
     """
diff --git a/backends/arm/test/passes/test_decompose_linear_pass.py b/backends/arm/test/passes/test_decompose_linear_pass.py
index 1bcd5d1a569..01f00c3e6b7 100644
--- a/backends/arm/test/passes/test_decompose_linear_pass.py
+++ b/backends/arm/test/passes/test_decompose_linear_pass.py
@@ -25,7 +25,7 @@ def get_example_inputs(self) -> Tuple[torch.Tensor]:
         return (torch.randn(1, 3, 16),)
 
 
-def test_decompose_linear_no_target_dynamic() -> None:
+def test_decompose_linear_dynamic() -> None:
     module = Linear()
     example_inputs = module.get_example_inputs()
     ep = export(
diff --git a/backends/arm/test/passes/test_fuse_consecutive_concat_shapes.py b/backends/arm/test/passes/test_fuse_consecutive_concat_shapes.py
index 544433c03ca..9cad9584684 100644
--- a/backends/arm/test/passes/test_fuse_consecutive_concat_shapes.py
+++ b/backends/arm/test/passes/test_fuse_consecutive_concat_shapes.py
@@ -83,7 +83,7 @@ def _run_fuse_pass(graph_module: GraphModule):
     return graph_module
 
 
-def test_fuse_consecutive_concat_shapes_no_target_flattens_nested_concat_inputs():
+def test_fuse_consecutive_concat_shapes_flattens_nested_concat_inputs():
     graph_module = _graph_module_with_nested_concat()
     graph_module = _run_fuse_pass(graph_module)
 
@@ -99,7 +99,7 @@ def test_fuse_consecutive_concat_shapes_no_target_flattens_nested_concat_inputs(
     )
 
 
-def test_fuse_consecutive_concat_shapes_no_target_leaves_flat_concat_unchanged():
+def test_fuse_consecutive_concat_shapes_leaves_flat_concat_unchanged():
     graph_module = _graph_module_with_flat_concat()
     graph_module = _run_fuse_pass(graph_module)
 
diff --git a/backends/arm/test/passes/test_insert_dynamic_padding_pass.py b/backends/arm/test/passes/test_insert_dynamic_padding_pass.py
index 01d2f7fd669..35b795ee2d9 100644
--- a/backends/arm/test/passes/test_insert_dynamic_padding_pass.py
+++ b/backends/arm/test/passes/test_insert_dynamic_padding_pass.py
@@ -26,7 +26,7 @@ def forward(self, x: torch.Tensor) -> torch.Tensor:
         return self.conv(x)
 
 
-def test_insert_dynamic_padding_no_target():
+def test_insert_dynamic_padding():
     model = ConvModule()
     example_inputs = (torch.randn(1, 3, 8, 8),)
     ep = export(
diff --git a/backends/arm/test/passes/test_replace_inf_values_pass.py b/backends/arm/test/passes/test_replace_inf_values_pass.py
index 0f4a069f3e3..8d6001c8df8 100644
--- a/backends/arm/test/passes/test_replace_inf_values_pass.py
+++ b/backends/arm/test/passes/test_replace_inf_values_pass.py
@@ -47,7 +47,7 @@ def _get_mask_buffer(graph_module: fx.GraphModule) -> torch.Tensor:
     return buffers["mask"]
 
 
-def test_replace_inf_and_limit_values_no_target_clamps_inf_constants():
+def test_replace_inf_and_limit_values_clamps_inf_constants():
     """Trace a module with infinities, run ReplaceInfAndLimitValuesPass, and
     expect the buffer and scalar literals to be clamped to ±255 with no
     infinities left.
@@ -64,7 +64,7 @@ def test_replace_inf_and_limit_values_no_target_clamps_inf_constants():
     assert sorted(_get_add_constants(result.graph_module)) == [-255, 255]
 
 
-def test_replace_inf_and_limit_values_no_target_respects_disallowed_nodes():
+def test_replace_inf_and_limit_values_respects_disallowed_nodes():
     """When nodes opt out of transforms, running the pass in TFA mode should
     leave the mask buffer untouched while still clamping scalar literals to
     ±255.
diff --git a/backends/arm/test/passes/test_rewrite_le_lt_to_ge_gt_pass.py b/backends/arm/test/passes/test_rewrite_le_lt_to_ge_gt_pass.py
index 781bc656be7..f3ed416fe0b 100644
--- a/backends/arm/test/passes/test_rewrite_le_lt_to_ge_gt_pass.py
+++ b/backends/arm/test/passes/test_rewrite_le_lt_to_ge_gt_pass.py
@@ -26,7 +26,7 @@ def forward(
 
 
 @common.parametrize("module", {"lt_le": LtLe()})
-def test_rewrite_le_lt_to_ge_gt_no_target(module: LtLe) -> None:
+def test_rewrite_le_lt_to_ge_gt(module: LtLe) -> None:
     pipeline = PassPipeline[input_t](
         module,
         module.get_inputs(),
diff --git a/backends/arm/test/passes/test_size_adjust_input_pass.py b/backends/arm/test/passes/test_size_adjust_input_pass.py
index 71e218e6816..e733ebcd849 100644
--- a/backends/arm/test/passes/test_size_adjust_input_pass.py
+++ b/backends/arm/test/passes/test_size_adjust_input_pass.py
@@ -46,7 +46,7 @@ def _needs_truncation(input_length, kernel_size, stride, padding):
     return _greater_than((input_length + 2 * padding - kernel_size) % stride, padding)
 
 
-def test_size_adjust_input_no_target_static_conv2d():
+def test_size_adjust_input_static_conv2d():
     kernel_size, stride, padding = 3, 3, 1
     model = ConvModule(kernel_size=kernel_size, stride=stride, padding=padding)
     example_inputs = (torch.randn(1, 3, 9, 9),)
@@ -77,7 +77,7 @@ def test_size_adjust_input_no_target_static_conv2d():
     ), "Input width should not need truncation after transformation"
 
 
-def test_size_adjust_input_no_target_static_conv_no_adjustment_needed():
+def test_size_adjust_input_static_conv_no_adjustment_needed():
     kernel_size, stride, padding = 3, 1, 1
     model = ConvModule(kernel_size=kernel_size, stride=stride, padding=padding)
     example_inputs = (torch.randn(1, 3, 9, 9),)
@@ -115,7 +115,7 @@ def test_size_adjust_input_no_target_static_conv_no_adjustment_needed():
     ), "No slice nodes should be inserted when no adjustment is needed"
 
 
-def test_size_adjust_input_no_target_dynamic_conv2d():
+def test_size_adjust_input_dynamic_conv2d():
     kernel_size, stride, padding = 3, 3, 1
     model = ConvModule(kernel_size=kernel_size, stride=stride, padding=padding)
     example_inputs = (torch.randn(1, 3, 14, 15),)
@@ -159,7 +159,7 @@ def test_size_adjust_input_no_target_dynamic_conv2d():
         ), "Two slice nodes should be inserted when adjustment is needed"
 
 
-def test_size_adjust_input_no_target_dynamic_conv_no_adjustment_needed():
+def test_size_adjust_input_dynamic_conv_no_adjustment_needed():
     kernel_size, stride, padding = 3, 1, 1
     model = ConvModule(kernel_size=kernel_size, stride=stride, padding=padding)
     example_inputs = (torch.randn(1, 3, 9, 9),)
@@ -227,7 +227,7 @@ def forward(self, x: torch.Tensor) -> torch.Tensor:
         return self.pool(x)
 
 
-def test_size_adjust_input_no_target_static_pooling():
+def test_size_adjust_input_static_pooling():
     kernel_size, stride, padding = 3, 3, 1
     model = PoolingModule(kernel_size=kernel_size, stride=stride, padding=padding)
     example_inputs = (torch.randn(1, 3, 9, 9),)
@@ -261,7 +261,7 @@ def test_size_adjust_input_no_target_static_pooling():
     ), "Input width should not need truncation after transformation"
 
 
-def test_size_adjust_input_no_target_static_pooling_no_adjustment_needed():
+def test_size_adjust_input_static_pooling_no_adjustment_needed():
     kernel_size, stride, padding = 3, 1, 1
     model = PoolingModule(kernel_size=kernel_size, stride=stride, padding=padding)
     example_inputs = (torch.randn(1, 3, 9, 9),)
@@ -303,7 +303,7 @@ def test_size_adjust_input_no_target_static_pooling_no_adjustment_needed():
     ), "No slice nodes should be inserted when no adjustment is needed"
 
 
-def test_size_adjust_input_no_target_dynamic_pooling():
+def test_size_adjust_input_dynamic_pooling():
     kernel_size, stride, padding = 3, 3, 1
     model = PoolingModule(kernel_size=kernel_size, stride=stride, padding=padding)
     example_inputs = (torch.randn(1, 3, 18, 18),)
@@ -355,7 +355,7 @@ def test_size_adjust_input_no_target_dynamic_pooling():
         ), "Two slice nodes should be inserted when adjustment is needed"
 
 
-def test_size_adjust_input_no_target_dynamic_pooling_no_adjustment_needed():
+def test_size_adjust_input_dynamic_pooling_no_adjustment_needed():
     kernel_size, stride, padding = 3, 1, 1
     model = PoolingModule(kernel_size=kernel_size, stride=stride, padding=padding)
     example_inputs = (torch.randn(1, 3, 18, 18),)
diff --git a/backends/arm/test/quantizer/test_partial_quantization.py b/backends/arm/test/quantizer/test_partial_quantization.py
index f8ba1d8d8d5..414d0c802fd 100644
--- a/backends/arm/test/quantizer/test_partial_quantization.py
+++ b/backends/arm/test/quantizer/test_partial_quantization.py
@@ -101,7 +101,7 @@ def _assert_disallow_flags(
         ), f"Node '{node_name}': expected DISALLOW_TFA_META_KEY={expected_flag}, got {actual_flag}"
 
 
-def test_disallow_tfa_for_skipped_module_no_target():
+def test_disallow_tfa_for_skipped_module():
     """Ensure a softmax skipped for quantization is not decomposed and that its
     node has `disallow_tfa` set.
     """
@@ -133,7 +133,7 @@ def example_inputs(self) -> tuple[torch.Tensor, ...]:
     )
 
 
-def test_disallow_tfa_for_two_skipped_modules_no_target():
+def test_disallow_tfa_for_two_skipped_modules():
     """Ensure a softmax and linear skipped for quantization are not decomposed
     and have their `disallow_tfa` set.
     """
@@ -156,7 +156,7 @@ def test_disallow_tfa_for_two_skipped_modules_no_target():
     )
 
 
-def test_disallow_tfa_with_global_none_and_one_quantized_module_no_target():
+def test_disallow_tfa_with_global_none_and_one_quantized_module():
     """Ensure that with a global None quantization config, only the linear
     module (with its own quantization config) is quantized, and that the other
     nodes have `disallow_tfa` set.
@@ -180,7 +180,7 @@ def test_disallow_tfa_with_global_none_and_one_quantized_module_no_target():
     )
 
 
-def test_disallow_tfa_for_submodule_by_name_no_target():
+def test_disallow_tfa_for_submodule_by_name():
     """Ensure submodules can be skipped for quantization by name and have their
     nodes marked as disallowed for TFA.
     """
@@ -203,7 +203,7 @@ def test_disallow_tfa_for_submodule_by_name_no_target():
     )
 
 
-def test_disallow_tfa_name_config_contradicts_type_config_no_target():
+def test_disallow_tfa_name_config_contradicts_type_config():
     """Ensure that module name configs take precedence over module type configs
     when they contradict each other.
     """