67 citations · 139 across the 12 of their papers we have counts for
4 papers · 1 filter
SelfCodeAlign: Self-Alignment for Code Generation
Yuxiang Wei, Federico Cassano, Jiawei Liu +7
Instruction tuning is a supervised fine-tuning approach that significantly improves the ability of large language models (LLMs) to follow human instructions. We propose SelfCodeAli…
Substance Beats Style: Why Beginning Students Fail to Code with LLMs
Francesca Lucchetti, Zixuan Wu, Arjun Guha +2
Although LLMs are increasing the productivity of professional programmers, existing work shows that beginners struggle to prompt LLMs to solve text-to-code tasks. Why is this the c…
StarCoder 2 and The Stack v2: The Next Generation
Anton Lozhkov, Raymond Li, Loubna Ben Allal +63
The BigCode project, an open-scientific collaboration focused on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder2. In partnership wi…
How Beginning Programmers and Code LLMs (Mis)read Each Other
Sydney Nguyen, Hannah McLean Babe, Yangtian Zi +3
Generative AI models, specifically large language models (LLMs), have made strides towards the long-standing goal of text-to-code generation. This progress has invited numerous stu…