Program-to-text Generation

Program-to-Text Generation is a natural language generation task that involves automatically generating human-readable textual descriptions from source code or executable programs, distinguishing it from other code-related generation tasks by focusing on natural language explanations of program functionality rather than code synthesis or translation.

116

Publications

10.3K

Citations

438

Authors

123

Institutions

Publications per year

2017–2026

76

Authors

438

  1. BR
    Baishakhi Ray

    Columbia University, United States

    5 publications · 1.1K citations

    5

    h-index

  2. SC
    Saikat Chakraborty

    Columbia University, United States

    5 publications · 1.1K citations

    5

    h-index

  3. SG
    Sumit Gulwani

    Microsoft (United States), United States

    5 publications · 1.3K citations

    5

    h-index

  4. GL
    Ge Li

    Peking University, China

    5 publications · 1.2K citations

    5

    h-index

  5. GN
    Graham Neubig

    Carnegie Mellon University, United States

    5 publications · 1K citations

    5

    h-index

1–5 of 438

Venues

  1. arXiv (Cornell University)

    Repository · 26 publications · 1.5K citations

    18

    h-index

  2. Journal of Systems and Software

    JSS · 3 publications · 88 citations

    3

    h-index

  3. ACM Transactions on Software Engineering and Methodology

    TOSEM · 3 publications · 154 citations

    3

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 2 publications · 67 citations

    2

    h-index

  5. National Conference on Artificial Intelligence

    Conference · 2 publications · 26 citations

    2

    h-index

1–5