We should emphasize that attention scores a i (1 ≤ i ≤ k) are learned along with other parts of the model in an end-to-end manner where they are optimized to capture the informativeness of the different sources at the fake news detection task.
capturing contributions of different sources reflected at scalar values a i (1 ≤ i ≤ k) makes the proposed framework somehow interpretable.