5 citations · 15 across the 25 of their papers we have counts for
7 papers · 1 filter
UCoder: Unsupervised Code Generation by Internal Probing of Large Language Models
Jiajun Wu, Jian Yang, Wei Zhang +6
Large language models (LLMs) have demonstrated remarkable capabilities in code generation tasks. However, their effectiveness heavily relies on supervised training with extensive l…
SimpleDevQA: Benchmarking Large Language Models on Development Knowledge QA
Jing Zhang, Lianghong Guo, Yanlin Wang +7
The Development Knowledge Question Answering (Dev Knowledge QA) task aims to provide natural language answers to knowledge-seeking questions during software development. To investi…
EffiReasonTrans: RL-Optimized Reasoning for Code Translation
Yanlin Wang, Rongyi Ou, Yanli Wang +6
Code translation is a crucial task in software development and maintenance. While recent advancements in large language models (LLMs) have improved automated code translation accur…
Towards Mitigating API Hallucination in Code Generated by LLMs with Hierarchical Dependency Aware
Yujia Chen, Mingyu Chen, Cuiyun Gao +3
Application Programming Interfaces (APIs) are crucial in modern software development. Large Language Models (LLMs) assist in automated code generation but often struggle with API h…
OmniGIRL: A Multilingual and Multimodal Benchmark for GitHub Issue Resolution
Lianghong Guo, Wei Tao, Runhan Jiang +7
The GitHub issue resolution task aims to resolve issues reported in repositories automatically. With advances in large language models (LLMs), this task has gained increasing atten…
Towards an Understanding of Context Utilization in Code Intelligence
Yanlin Wang, Kefeng Duan, Dewu Zheng +9
Code intelligence is an emerging domain in software engineering, aiming to improve the effectiveness and efficiency of various code-related tasks. Recent research suggests that inc…
What to Retrieve for Effective Retrieval-Augmented Code Generation? An Empirical Study and Beyond
Wenchao Gu, Juntao Chen, Yanlin Wang +6
Repository-level code generation remains challenging due to complex code dependencies and the limitations of large language models (LLMs) in processing long contexts. While retriev…