activity
20242026
most citedAcTracer: Active Testing of Large Language Model via Multi-Stage Sampling

1 citations · 1 across the 12 of their papers we have counts for

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7 papers · 1 filter

cs.SE2026

Graph-Aware Fuzzing for Graph Database Management Systems

Yu Li, Qiang Hu, Yao Zhang +4

Graph Database Management Systems (GDBMSs) are essential infrastructure for managing interconnected data. Existing GDBMS testing methods primarily rely on differential and metamorp…

cs.SE2026

Human in the Loop for Fuzz Testing: Literature Review and the Road Ahead

Jiongchi Yu, Xiaolin Wen, Sizhe Cheng +3

Fuzz testing is one of the most effective techniques for detecting bugs and vulnerabilities in software. However, as the basis of fuzz testing, automated heuristics often fail to u…

cs.SE2025

Defects4C: Benchmarking Large Language Model Repair Capability with C/C++ Bugs

Jian Wang, Xiaofei Xie, Qiang Hu +4

Automated Program Repair (APR) plays a critical role in enhancing the quality and reliability of software systems. While substantial progress has been made in Java-based APR, large…

cs.SE2025

Do Code Semantics Help? A Comprehensive Study on Execution Trace-Based Information for Code Large Language Models

Jian Wang, Xiaofei Xie, Qiang Hu +2

Code Large Language Models (Code LLMs) have opened a new era in programming with their impressive capabilities. However, recent research has revealed critical limitations in their…

cs.SE2025

Understanding the Supply Chain and Risks of Large Language Model Applications

Yujie Ma, Lili Quan, Xiaofei Xie +4

The rise of Large Language Models (LLMs) has led to the widespread deployment of LLM-based systems across diverse domains. As these systems proliferate, understanding the risks ass…

cs.SE2025

Foundation Models for Autonomous Driving System: An Initial Roadmap

Xiongfei Wu, Mingfei Cheng, Xiaoning Ren +8

Recent advances in foundation models (FMs), including large language models (LLMs), vision-language models (VLMs), and world models, have opened new opportunities for autonomous dr…

cs.SE2024★ 1 cited

AcTracer: Active Testing of Large Language Model via Multi-Stage Sampling

Yuheng Huang, Jiayang Song, Qiang Hu +2

Performance evaluation plays a crucial role in the development life cycle of large language models (LLMs). It estimates the model's capability, elucidates behavior characteristics,…