200 citations · 336 across the 9 of their papers we have counts for
9 papers
AgentPack: A Dataset of Code Changes, Co-Authored by Agents and Humans
Yangtian Zi, Zixuan Wu, Aleksander Boruch-Gruszecki +2
Fine-tuning large language models for code editing has typically relied on mining commits and pull requests. The working hypothesis has been that commit messages describe human int…
More Than a Score: Probing the Impact of Prompt Specificity on LLM Code Generation
Yangtian Zi, Harshitha Menon, Arjun Guha
State-of-the-art Large Language Models (LLMs) achieve high pass@1 on general benchmarks like HumanEval but underperform on specialized suites such as ParEval. Is this due to LLMs m…
Agnostics: Learning to Code in Any Programming Language via Reinforcement with a Universal Learning Environment
Aleksander Boruch-Gruszecki, Yangtian Zi, Zixuan Wu +4
Large language models (LLMs) already excel at writing code in high-resource languages such as Python and JavaScript, yet stumble on low-resource languages that remain essential to…
"I Would Have Written My Code Differently'': Beginners Struggle to Understand LLM-Generated Code
Yangtian Zi, Luisa Li, Arjun Guha +2
Large language models (LLMs) are being increasingly adopted for programming work. Prior work shows that while LLMs accelerate task completion for professional programmers, beginnin…
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…
StudentEval: A Benchmark of Student-Written Prompts for Large Language Models of Code
Hannah McLean Babe, Sydney Nguyen, Yangtian Zi +3
Code LLMs are being rapidly deployed and there is evidence that they can make professional programmers more productive. Current benchmarks for code generation measure whether model…
StarCoder: may the source be with you!
Raymond Li, Loubna Ben Allal, Yangtian Zi +64
The BigCode community, an open-scientific collaboration working on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder and StarCoderBase…
SantaCoder: don't reach for the stars!
Loubna Ben Allal, Raymond Li, Denis Kocetkov +38
The BigCode project is an open-scientific collaboration working on the responsible development of large language models for code. This tech report describes the progress of the col…
MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation
Federico Cassano, John Gouwar, Daniel Nguyen +10
Large language models have demonstrated the ability to generate both natural language and programming language text. Such models open up the possibility of multi-language code gene…