The choice of compositional operator (tensorbased or a simple point-wise operation) depends strongly on the task and dataset: tensor-based composition performed best with the verb disambiguation task, where the verb senses depend strongly on the arguments of the verb.
it seems to depend less on the nature of the vectors itself: in the disambiguation task, tensor-based composition proved best for both co-occurrencebased and neural vectors; in the sentence similarity task, where point-wise operators proved best, this was again true across vector spaces.