Task: Language Identification
Input (Spanish, English): This paper proposed an iterative query updating mechanism for cloze-style QA. The approach is novel and interesting and while it is only verified in the paper for two Cloze-style tasks (CBT and WDW), the concept of read/compose/write operations seem to be more general and can be potentially applied to other reasoning tasks beyond Cloze-style QA. Another advantage of the proposed model is to learn when to terminate the iteration by the so-called adaptive computation model, such that it avoids the issue of treating the number of iterations as another hyper-parameter, which is a common practice of iterative models/multi-hop reasoning in previous papers.  There are a couple places that this paper can improve. First, I would like to see the results from CNN/Daily Mail as well to have a more comprehensive comparison. Secondly, it will be useful to visualize the entire M^q sequence over time t (not just z or the query gating) to help understand better the query regression and if it is human interpretable.
Output (English): en