3 papers
cs.SE2025
BASFuzz: Towards Robustness Evaluation of LLM-based NLP Software via Automated Fuzz Testing
Mingxuan Xiao, Yan Xiao, Shunhui Ji +2
Fuzzing has shown great success in evaluating the robustness of intelligent natural language processing (NLP) software. As large language model (LLM)-based NLP software is widely d…
cs.SE2025
Assessing the Robustness of LLM-based NLP Software via Automated Testing
Mingxuan Xiao, Yan Xiao, Shunhui Ji +3
Benefiting from the advancements in LLMs, NLP software has undergone rapid development. Such software is widely employed in various safety-critical tasks, such as financial sentime…
cs.SE2025
ABFS: Natural Robustness Testing for LLM-based NLP Software
Mingxuan Xiao, Yan Xiao, Shunhui Ji +3
Owing to the exceptional performance of Large Language Models (LLMs) in Natural Language Processing (NLP) tasks, LLM-based NLP software has rapidly gained traction across various d…