11 citations · 20 across the 9 of their papers we have counts for
4 papers · 1 filter
The KoLMogorov Test: Compression by Code Generation
Ori Yoran, Kunhao Zheng, Fabian Gloeckle +3
Compression is at the heart of intelligence. A theoretically optimal way to compress any sequence of data is to find the shortest program that outputs that sequence and then halts.…
Better & Faster Large Language Models via Multi-token Prediction
Fabian Gloeckle, Badr Youbi Idrissi, Baptiste Rozière +2
Large language models such as GPT and Llama are trained with a next-token prediction loss. In this work, we suggest that training language models to predict multiple future tokens…
Decoding Data Quality via Synthetic Corruptions: Embedding-guided Pruning of Code Data
Yu Yang, Aaditya K. Singh, Mostafa Elhoushi +7
Code datasets, often collected from diverse and uncontrolled sources such as GitHub, potentially suffer from quality issues, thereby affecting the performance and training efficien…
Code Llama: Open Foundation Models for Code
Baptiste Rozière, Jonas Gehring, Fabian Gloeckle +23
We release Code Llama, a family of large language models for code based on Llama 2 providing state-of-the-art performance among open models, infilling capabilities, support for lar…