NatGen: Generative pre-training by "Naturalizing" source code. (arXiv:2206.07585v1 [cs.PL])

Pre-trained Generative Language models (e.g. PLBART, CodeT5, SPT-Code) for
source code yielded strong results on several tasks in the past few years,
including code generation and translation. These models have adopted varying
pre-training objectives to learn statistics of code construction from very
large-scale corpora in a self-supervised fashion; the success of pre-trained
models largely hinges on these pre-training objectives. This paper proposes a
new pre-training objective, "Naturalizing" of source code, exploiting code's
bimodal, dual-channel (formal & natural channels) nature. Unlike …

arxiv code pl pre-training training