diff --git a/.github/workflows/python-package.yml b/.github/workflows/python-package.yml
index 6164b04..f11e4f6 100644
--- a/.github/workflows/python-package.yml
+++ b/.github/workflows/python-package.yml
@@ -12,8 +12,8 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.8", "3.9", "3.10"]
-        torch-version: ["1.13.1", "2.0.1"]
+        python-version: ["3.8", "3.10", "3.12"]
+        torch-version: ["1.13.1", "2.4.1"]
 
     steps:
     - uses: actions/checkout@v3
diff --git a/torchsparsegradutils/indexed_matmul.py b/torchsparsegradutils/indexed_matmul.py
index 298fd6b..f6dc153 100644
--- a/torchsparsegradutils/indexed_matmul.py
+++ b/torchsparsegradutils/indexed_matmul.py
@@ -27,6 +27,9 @@ def segment_mm(a, b, seglen_a):
     Returns:
         torch.Tensor: The output dense matrix of shape ``(N, D2)``
     """
+    if torch.__version__ < (2, 4):
+        raise NotImplementedError("PyTorch version is too old for nested tesors")
+
     if dgl_installed:
         # DGL is probably more computationally efficient
         # See https://github.com/pytorch/pytorch/issues/136747
@@ -74,6 +77,9 @@ def gather_mm(a, b, idx_b):
     Returns:
         torch.Tensor: The output dense matrix of shape ``(N, D2)``
     """
+    if torch.__version__ < (2, 4):
+        raise NotImplementedError("PyTorch version is too old for nested tesors")
+
     if dgl_installed:
         # DGL is more computationally efficient
         # See https://github.com/pytorch/pytorch/issues/136747
diff --git a/torchsparsegradutils/tests/test_indexed_matmul.py b/torchsparsegradutils/tests/test_indexed_matmul.py
index 491f143..7c9a527 100644
--- a/torchsparsegradutils/tests/test_indexed_matmul.py
+++ b/torchsparsegradutils/tests/test_indexed_matmul.py
@@ -1,6 +1,11 @@
 import torch
 import pytest
 
+if torch.__version__ < (2, 4):
+    pytest.skip(
+        "Skipping test based on nested tensors since an old version of pytorch is used", allow_module_level=True
+    )
+
 from torchsparsegradutils import gather_mm, segment_mm
 
 # Identify Testing Parameters