We suspect that this is because this headline contains three keywords "syria", "civil", "war", and also the key date information: the model was trained partly on the Libya war timeline, and therefore many features and parameters were activated in the matrix factorization framework to give a high recommendation in this testing scenario.
when evaluating the output of the joint text and vision system, we see that this error is eliminated: the selected sentence on 2011-12-02 is "Eleven killed after weekly prayers in Syria on eve of Arab League deadline".