Talk
Neural Code Generation Models with Programming Language Knowledge
Code generation is one of the most promising applications of LLMs. However, programs are naturally symbolic product, with symbolic knowledge such as grammars, type systems, and semantics. Learning such knowledge purely from data is difficult. In this talk I will report the work done in Peking University which guides neural models to learn the programming language knowledge, so as to enhance the performance of code models.