5 papers
Evaluating Implicit Regulatory Compliance in LLM Tool Invocation via Logic-Guided Synthesis
Da Song, Yuheng Huang, Boqi Chen +4
The integration of large language models (LLMs) into autonomous agents has enabled complex tool use, yet in high-stakes domains, these systems must strictly adhere to regulatory st…
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…
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…
Towards Understanding the Characteristics of Code Generation Errors Made by Large Language Models
Zhijie Wang, Zijie Zhou, Da Song +4
Large Language Models (LLMs) have demonstrated unprecedented capabilities in code generation. However, there remains a limited understanding of code generation errors that LLMs can…
TESTEVAL: Benchmarking Large Language Models for Test Case Generation
Wenhan Wang, Chenyuan Yang, Zhijie Wang +6
Testing plays a crucial role in the software development cycle, enabling the detection of bugs, vulnerabilities, and other undesirable behaviors. To perform software testing, teste…