6 papers
The Devil Is in the Interface: Evaluating How Tool Architecture Shapes Coding Agent Behavior
Xiangzhe Xu, Hamidreza Saghir, Qianhui Wu +5
As large language models continue to improve, agentic systems are becoming increasingly important, and tools are a key design dimension because they determine how agents access inf…
SpecOps: A Fully Automated AI Agent Testing Framework in Real-World GUI Environments
Syed Yusuf Ahmed, Shiwei Feng, Chanwoo Bae +1
Autonomous AI agents powered by large language models (LLMs) are increasingly deployed in real-world applications, where reliable and robust behavior is critical. However, existing…
TAI3: Testing Agent Integrity in Interpreting User Intent
Shiwei Feng, Xiangzhe Xu, Xuan Chen +5
LLM agents are increasingly deployed to automate real-world tasks by invoking APIs through natural language instructions. While powerful, they often suffer from misinterpretation o…
SOFT: Selective Data Obfuscation for Protecting LLM Fine-tuning against Membership Inference Attacks
Kaiyuan Zhang, Siyuan Cheng, Hanxi Guo +8
Large language models (LLMs) have achieved remarkable success and are widely adopted for diverse applications. However, fine-tuning these models often involves private or sensitive…
LLM Agents Should Employ Security Principles
Kaiyuan Zhang, Zian Su, Pin-Yu Chen +3
Large Language Model (LLM) agents show considerable promise for automating complex tasks using contextual reasoning; however, interactions involving multiple agents and the system'…
CodeMirage: A Multi-Lingual Benchmark for Detecting AI-Generated and Paraphrased Source Code from Production-Level LLMs
Hanxi Guo, Siyuan Cheng, Kaiyuan Zhang +2
Large language models (LLMs) have become integral to modern software development, producing vast amounts of AI-generated source code. While these models boost programming productiv…