AlphaCode: A System for Code Generation

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Machine Learning

Artificial Intelligence

Programming Languages

AlphaCode: A System for Code Generation

Competition-Level Code Generation with AlphaCode

We introduce alphacode, a system for code generation that can create novel solutions to competitive programming problems that require deeper reasoning.

The system was evaluated on simulated evaluations on recent programming competitions on the codeforces platform, and achieved on average a ranking of top 54.3% in competitions with morethan 5,000 participants.

We found that three key components were critical toachieve good and reliable performance : (1) an extensive and clean competitive programming dataset for training and evaluation, (2) large and efficient-to-sample transformer-based architectures, and (3) large-scale model sampling to explore the search space, followed by filtering based on programbehavior to a small set of submissions.

Authors

Yujia Li, David Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, Thomas Hubert, Peter Choy, Cyprien de Masson d'Autume, Igor Babuschkin, Xinyun Chen, Po-Sen Huang, Johannes Welbl, Sven Gowal, Alexey Cherepanov, James Molloy

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