text: The authors build on the work of Tang et al. (2017),  who made a minor change to the skip-thought model by decoding only the next sentence, rather than the previous one also.  The additional minor change in this paper is to use a CNN, rather than RNN, decoder. I am sympathetic to the goals of the work, and believe this sort of work should be carried out,  but I see the contribution as too minor to constitute a paper at the conference track of a leading international conference such as ICLR.  Given the incremental nature of the work, I think this would be a good fit for something like a short paper at *ACL. I found the more theoretical motivation of the CNN decoder not terribly convincing, and somewhat post-hoc.  I feel as though analogous arguments could just as easily be made for an RNN decoder.  Ultimately I see these questions - such as CNN vs. RNN for the decoder - as empirical ones. Finally, the authors have admirably attempted a thorough comparison with existing work, in the related work section,  but this section takes up a large chunk of the paper at the end,  and again I would have preferred this section to be much shorter and more concise. Summary: worthwhile empirical goal,  but the paper could have been easily written using half as much space.