diff --git a/optimum/exporters/tasks.py b/optimum/exporters/tasks.py
index 242f85ab301..2841383eb96 100644
--- a/optimum/exporters/tasks.py
+++ b/optimum/exporters/tasks.py
@@ -301,8 +301,10 @@ class TasksManager:
             "text-generation-with-past",
             "text2text-generation",
             "text2text-generation-with-past",
-            "text-classification",
-            "question-answering",
+            # text-classification and question-answering can be supported, but the ONNX export is currently broken due to a regression in PyTorch 2.1.
+            # Reference: https://github.com/pytorch/pytorch/issues/110597.
+            # "text-classification",
+            # "question-answering",
             onnx="BartOnnxConfig",
         ),
         # BEiT cannot be used with the masked image modeling autoclass, so this task is excluded here
diff --git a/tests/onnxruntime/test_modeling.py b/tests/onnxruntime/test_modeling.py
index d265e2e7cf9..8f2dcb7d34a 100644
--- a/tests/onnxruntime/test_modeling.py
+++ b/tests/onnxruntime/test_modeling.py
@@ -1055,7 +1055,7 @@ def test_trust_remote_code(self):
 class ORTModelForQuestionAnsweringIntegrationTest(ORTModelTestMixin):
     SUPPORTED_ARCHITECTURES = [
         "albert",
-        "bart",
+        # "bart",  # see tasks.py
         "bert",
         # "big_bird",
         # "bigbird_pegasus",
@@ -1372,7 +1372,7 @@ def test_compare_to_io_binding(self, model_arch):
 class ORTModelForSequenceClassificationIntegrationTest(ORTModelTestMixin):
     SUPPORTED_ARCHITECTURES = [
         "albert",
-        "bart",
+        # "bart",  # see tasks.py
         "bert",
         # "big_bird",
         # "bigbird_pegasus",
diff --git a/tests/onnxruntime/test_optimization.py b/tests/onnxruntime/test_optimization.py
index cd2127ac3be..6bc8d49fed5 100644
--- a/tests/onnxruntime/test_optimization.py
+++ b/tests/onnxruntime/test_optimization.py
@@ -89,7 +89,6 @@ def tearDownClass(cls):
 class ORTOptimizerTest(unittest.TestCase):
     # Contribution note: Please add test models in alphabetical order. Find test models here: https://huggingface.co/hf-internal-testing.
     SUPPORTED_ARCHITECTURES_WITH_MODEL_ID = (
-        (ORTModelForSequenceClassification, "hf-internal-testing/tiny-random-bart"),
         (ORTModelForSequenceClassification, "hf-internal-testing/tiny-random-bert"),
         # (ORTModelForSequenceClassification, "hf-internal-testing/tiny-random-big_bird"),
         (ORTModelForSequenceClassification, "hf-internal-testing/tiny-random-distilbert"),
diff --git a/tests/onnxruntime/test_quantization.py b/tests/onnxruntime/test_quantization.py
index 4062c556ea9..4736ee90415 100644
--- a/tests/onnxruntime/test_quantization.py
+++ b/tests/onnxruntime/test_quantization.py
@@ -76,7 +76,6 @@ class ORTDynamicQuantizationTest(unittest.TestCase):
         (ORTModelForSequenceClassification, "hf-internal-testing/tiny-random-bert", 30),
         (ORTModelForSequenceClassification, "hf-internal-testing/tiny-random-roberta", 30),
         (ORTModelForSequenceClassification, "hf-internal-testing/tiny-random-distilbert", 30),
-        (ORTModelForSequenceClassification, "hf-internal-testing/tiny-random-bart", 32),
     )
 
     SUPPORTED_DECODER_ARCHITECTURES_WITH_EXPECTED_QUANTIZED_MATMULS = (