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cs.SE2024
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.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…