54 citations · 107 across the 13 of their papers we have counts for
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cs.SE2022★ 8 cited
Probing Pretrained Models of Source Code
Sergey Troshin, Nadezhda Chirkova
Deep learning models are widely used for solving challenging code processing tasks, such as code generation or code summarization. Traditionally, a specific model architecture was…
cs.SE2020
On the Embeddings of Variables in Recurrent Neural Networks for Source Code
Nadezhda Chirkova
Source code processing heavily relies on the methods widely used in natural language processing (NLP), but involves specifics that need to be taken into account to achieve higher q…
cs.SE2020★ 1 cited
A Simple Approach for Handling Out-of-Vocabulary Identifiers in Deep Learning for Source Code
Nadezhda Chirkova, Sergey Troshin
There is an emerging interest in the application of natural language processing models to source code processing tasks. One of the major problems in applying deep learning to softw…