Task: Language Identification
Input (Spanish, English): Thanks for the response. I look forward to reading about the effect of incentives and the ambiguity of the language in the domain.  Review before author response: The paper proposes a way to build natural language interfaces by allowing a set of users to define new concepts and syntax. It's an (non-trivial) extension of S. I. Wang, P. Liang, and C. Manning. 2016. Learning language games through interaction  Questions: - What is the size of the vocabulary used  - Is it possible to position this paper with respect to previous work on inverse reinforcement learning and imitation learning ?  Strengths: - The paper is well written - It provides a compelling direction/solution to the problem of dealing with a large set of possible programs while learning natural language interfaces.   Weaknesses: - The authors should discuss the effect of the incentives on the final performance ? Were other alternatives considered ?  - While the paper claims that the method can be extended to more practical domains, it is not clear to me how straightforward it is going to be. How sensitive is the method to the size of the vocabulary required in a domain ? Would increased ambiguity in natural language create new problems ? These questions are not discussed in the current experiments. - A real-world application would definitely strengthen the paper even more.
Output (English): en