most citedEvaluating Large Language Models Trained on Code

1.5k citations · 1.7k across the 2 of their papers we have counts for

collaborators

2 papers

cs.CY2022★ 196 cited

Predictability and Surprise in Large Generative Models

Deep Ganguli, Danny Hernandez, Liane Lovitt +27

Large-scale pre-training has recently emerged as a technique for creating capable, general purpose, generative models such as GPT-3, Megatron-Turing NLG, Gopher, and many others. I…

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…