most citedEvaluating Large Language Models Trained on Code

1.5k citations · 1.5k across the 2 of their papers we have counts for

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2 papers

cs.LG2022★ 81 cited

Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets

Alethea Power, Yuri Burda, Harri Edwards +2

In this paper we propose to study generalization of neural networks on small algorithmically generated datasets. In this setting, questions about data efficiency, memorization, gen…

cs.LG2021★ 1.5k cited

Evaluating Large Language Models Trained on Code

Mark Chen, Jerry Tworek, Heewoo Jun +55

We introduce Codex, a GPT language model fine-tuned on publicly available code from GitHub, and study its Python code-writing capabilities. A distinct production version of Codex p…