diff --git a/docs/source/examples/index.rst b/docs/source/examples/index.rst
index 9d0c4884..603c8a3f 100644
--- a/docs/source/examples/index.rst
+++ b/docs/source/examples/index.rst
@@ -20,8 +20,7 @@ This section contains some usage examples for TorchJD.
   dedicated backpropagation function :doc:`mtl_backward <../docs/autojac/mtl_backward>`.
 - :doc:`Instance-Wise Multi-Task Learning (IWMTL) <iwmtl>` shows how to combine multi-task learning
   with instance-wise risk minimization: one loss per task and per element of the batch, using the
-  :doc:`autogram.Engine <../docs/autogram/engine>` and a :doc:`GeneralizedWeighting
-  <../docs/aggregation/index>`.
+  :doc:`autogram.Engine <../docs/autogram/engine>`.
 - :doc:`Recurrent Neural Network (RNN) <rnn>` shows how to apply Jacobian descent to RNN training,
   with one loss per output sequence element.
 - :doc:`Monitoring Aggregations <monitoring>` shows how to monitor the aggregation performed by the