Review for NeurIPS paper: Neural Execution Engines: Learning to Execute Subroutines

After reading each others reviews and discussing the author rebuttal, opinions on this submission sit around the borderline. The hesitation towards acceptance largely comes from a confusion around the key motivations of the work, the amount of important details residing in the supplement, and uncertainty around the relationship to prior work in program synthesis. The work focus on strong generalization in neural networks trained to perform algorithmic reasoning. The experiments focus on generalization in a fairly narrow domain -- algorithmic subroutines such as finding the minimum of a list, merging two sorted lists, taking a sum, etc. And the type of generalization examined is concerned with extending the length of the input list by scaling up the associated problem (sorting, MST, shortest path) and generalizing to never-before seen numbers or number combinations.