1. For the captioning experiment, the paper compares to related work only on some not official test set or dev set, however the final results should be compared on the official COOC leader board on the blind test set: https://competitions.codalab.org/competitions/3221#results e.g. [5,17] have won this challenge and have been evaluated on the blind challenge set. Also, several other approaches have been proposed since then and significantly improved (see leaderboard, the paper should at least compare to the once where an corresponding publication is available). 2. A human evaluation for caption generation would be more convincing as the automatic evaluation metrics can be misleading. 3. It is not clear from Section 4.2 how the supervision is injected for the source code caption experiment. While it is over interesting work, for acceptance at least points 1 and 3 of the weaknesses have to be addressed. ==== post author response === The author promised to include the results from 1. in the final For 3. it would be good to state it explicitly in Section section 4.2. I encourage the authors to include the additional results they provided in the rebuttal, e.g. T_r in the final version, as it provides more insight in the approach. Mine and, as far as I can see, the other reviewers concerns have been largely addressed, I thus recommend to accept the paper.
2. A human evaluation for caption generation would be more convincing as the automatic evaluation metrics can be misleading.