text: In this paper, the authors studied the problem of semi-supervised few-shot classification, by extending the prototypical networks into the setting of semi-supervised learning with examples from distractor classes.   The studied problem is interesting,  and the paper is well-written.  Extensive experiments are performed to demonstrate the effectiveness of the proposed methods.   While the proposed method is a natural extension of the existing works (i.e., soft k-means and meta-learning). On top of that, It seems the authors have over-claimed their model capability at the first place  as the proposed model cannot properly classify the distractor examples but just only consider them as a single class of outliers.  Overall, I would like to vote for a weakly acceptance regarding this paper.