1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.SE2024
RITFIS: Robust input testing framework for LLMs-based intelligent software
Mingxuan Xiao, Yan Xiao, Hai Dong +2
The dependence of Natural Language Processing (NLP) intelligent software on Large Language Models (LLMs) is increasingly prominent, underscoring the necessity for robustness testin…
cs.SE2023★ 1 cited
Empirical Study on Transformer-based Techniques for Software Engineering
Yan Xiao, Xinyue Zuo, Lei Xue +3
Many Transformer-based pre-trained models for code have been developed and applied to code-related tasks. In this paper, we review the existing literature, examine the suitability…
cs.SE2023
LEAP: Efficient and Automated Test Method for NLP Software
Mingxuan Xiao, Yan Xiao, Hai Dong +2
The widespread adoption of DNNs in NLP software has highlighted the need for robustness. Researchers proposed various automatic testing techniques for adversarial test cases. Howev…