12 citations · 39 across the 18 of their papers we have counts for
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cs.SE2025
TRUSTVIS: A Multi-Dimensional Trustworthiness Evaluation Framework for Large Language Models
Ruoyu Sun, Da Song, Jiayang Song +2
As Large Language Models (LLMs) continue to revolutionize Natural Language Processing (NLP) applications, critical concerns about their trustworthiness persist, particularly in saf…
cs.SE2025
Evaluating LLMs on Sequential API Call Through Automated Test Generation
Yuheng Huang, Jiayang Song, Da Song +4
By integrating tools from external APIs, Large Language Models (LLMs) have expanded their promising capabilities in a diverse spectrum of complex real-world tasks. However, testing…
cs.SE2025★ 2 cited
Risk Assessment Framework for Code LLMs via Leveraging Internal States
Yuheng Huang, Lei Ma, Keizaburo Nishikino +1
The pre-training paradigm plays a key role in the success of Large Language Models (LLMs), which have been recognized as one of the most significant advancements of AI recently. Bu…