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Xiaoning Du

10 papers hereh-index 5114 citations14 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author8
  • last author2

Across the 10 of 10 papers where every author was matched, so the position is known.

fields
  • cs.SE10
same name
  • Xiaoning Du — 12 papers, h 14
  • Xiaoning Du — 6 papers, h 2
  • Xiaoning Du — 6 papers, h 2
  • Xiaoning Du — 2 papers, h 4
  • Xiaoning Du — 2 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232025
most citedPop Quiz! Do Pre-trained Code Models Possess Knowledge of Correct API Names?

1 citations · 1 across the 9 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.SE2024

FDI: Attack Neural Code Generation Systems through User Feedback Channel

Zhensu Sun, Xiaoning Du, Xiapu Luo +3

Neural code generation systems have recently attracted increasing attention to improve developer productivity and speed up software development. Typically, these systems maintain a…

cs.SE2024

Towards Agentic Runtime Healing

Zhensu Sun, Haotian Zhu, Bowen Xu +3

Self-healing systems have long been a focus of research, aiming to enable software to recover from unexpected runtime errors without human intervention. Traditional approaches rely…

cs.SE2024

AI Coders Are Among Us: Rethinking Programming Language Grammar Towards Efficient Code Generation

Zhensu Sun, Xiaoning Du, Zhou Yang +2

Artificial Intelligence (AI) models have emerged as another important audience for programming languages alongside humans and machines, as we enter the era of large language models…

cs.SE2024

When Neural Code Completion Models Size up the Situation: Attaining Cheaper and Faster Completion through Dynamic Model Inference

Zhensu Sun, Xiaoning Du, Fu Song +2

Leveraging recent advancements in large language models, modern neural code completion models have demonstrated the capability to generate highly accurate code suggestions. However…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.