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Transforming a graphical user interface screenshot created by a designer into computer code is a typical task conducted by a developer in order to build customized software, websites, and mobile applications.
We present TRANX, a transition-based neural semantic parser that maps natural language (NL) utterances into formal meaning representations (MRs).
SOTA for Semantic Parsing on ATIS
Semantic parsing is the task of transducing natural language (NL) utterances into formal meaning representations (MRs), commonly represented as tree structures.
Automated documentation of programming source code and automated code generation from natural language are challenging tasks of both practical and scientific interest.
Results are presented for a case study of targeting the Qualcomm Snapdragon 820 mobile computing platform for CNN deployment.