Finally, we rank the candidates using the scores in our in-context paraphrase vectors from Section 6.2.
this time we check the effect of injecting a stronger bias towards the given context c, by averaging only the top-m percent contexts most similar to c, for m ∈ {1%, 5%, 10%, 100%}, as described in Section 4.2.