Thus, to compute the loss, we project the chunk scores z i,j,l for an aligned chunk pair (s i , t j , l) to the tokens that constitute the chunks by equally partitioning the scores among all possible internal alignments.
for a token w i in the chunk s i and token w j in chunk s j , we define token similarity scores as Here, the normalizing function N is the product of the number of tokens in the chunks 3 .