Specifically, for the word-level co-attention model CAN w : For the sentence-level co-attention model For the hierarchical co-attention model HCAN in Figure 2, the outputs of the word and sentence level layer are merged together to generate the final results.
the final similarity score between i-th gloss and context is computed as the weighted sum of word-level score β w i and sentence-level score β s i : Meanwhile, the final context embedding vector is also generated by a combination of two levels' context embedding vector:ĉ w andĉ s .