2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.SE2026
CangjieBench: Benchmarking LLMs on a Low-Resource General-Purpose Programming Language
Junhang Cheng, Fang Liu, Jia Li +3
Large Language Models excel in high-resource programming languages but struggle with low-resource ones. Existing research related to low-resource programming languages primarily fo…
cs.SE2024★ 1 cited
A Deep Dive into Large Language Models for Automated Bug Localization and Repair
Soneya Binta Hossain, Nan Jiang, Qiang Zhou +5
Large language models (LLMs) have shown impressive effectiveness in various software engineering tasks, including automated program repair (APR). In this study, we take a deep dive…
cs.CL2024★ 2 cited
LeDex: Training LLMs to Better Self-Debug and Explain Code
Nan Jiang, Xiaopeng Li, Shiqi Wang +6
In the domain of code generation, self-debugging is crucial. It allows LLMs to refine their generated code based on execution feedback. This is particularly important because gener…