1 citations · 1 across the 14 of their papers we have counts for
18 papers
Split Conformal Interval Length under Huber Contamination
Xiao Zhang, Bowen Zhang, Lie He
Existing analyses of interval length in split conformal prediction largely focus on clean data. However, how contamination at the training and calibration stages alters interval le…
AgentTrap: Stateful Feedback Deception against Autonomous Penetration Testing Agents
Yuelin Wang, Jiongchi Yu, Yanbang Sun
Autonomous penetration testing agents conduct multi-step attacks by continuously adapting their plans and actions to target responses. As a common defense, honeypots can be deploye…
AdaRepair-Mem: Adaptive Experience Orchestration for Repository-Level Program Repair
Z. C. Luo, J. C. Guo, W. J. He +10
Recent memory-augmented repository-level program repair methods reuse historical repair experiences to improve LLM-based issue resolution. However, our analysis reveals three limit…
Repair or Resample? Rethinking Failure Debugging in LLM Multi-Agent Systems
Zhongwen Luan, Xiaoyu Zhang, Ming Hu +3
As large language model (LLM)-based multi-agent systems (MASs) are increasingly applied to long-horizon complex tasks, their reliability has emerged as the core bottleneck hinderin…
AgentAntibody: An Adaptive Immune System for Defending LLM Agents against Prompt Injection
Shihao Weng, Yang Feng, Xiaofei Xie +1
Prompt injection remains a critical threat to LLM agents, yet existing defenses treat each task as a self-contained problem, independent of previous encounters. In practice, user r…
ARGUS: Defending LLM Agents Against Context-Aware Prompt Injection
Shihao Weng, Yang Feng, Jinrui Zhang +3
Large Language Model (LLM) agents are increasingly deployed as task-oriented software systems that use runtime context to decide and act on behalf of users. This delegation model m…
Weaponizing the Commons: A Taxonomy and Detection Framework of Abuse on GitHub
Yuli Cheng, Xiaoyu Zhang, Jiongchi Yu +3
GitHub plays a critical role in modern software supply chains, making its security an important research concern. Existing studies have primarily focused on CI/CD automation, colla…
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…
DynaTrust: Defending Multi-Agent Systems Against Sleeper Agents via Dynamic Trust Graphs
Yu Li, Qiang Hu, Yao Zhang +3
Large Language Model-based Multi-Agent Systems (MAS) have demonstrated remarkable collaborative reasoning capabilities but introduce new attack surfaces, such as the sleeper agent,…
PTCBENCH: Benchmarking Contextual Stability of Personality Traits in LLM Systems
Jiongchi Yu, Yuhan Ma, Xiaoyu Zhang +4
With the increasing deployment of large language models (LLMs) in affective agents and AI systems, maintaining a consistent and authentic LLM personality becomes critical for user…
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…
AutoEmpirical: LLM-Based Automated Research for Empirical Software Fault Analysis
Jiongchi Yu, Weipeng Jiang, Xiaoyu Zhang +3
Understanding software faults is essential for empirical research in software development and maintenance. However, traditional fault analysis, while valuable, typically involves m…
Leveraging LLM Agents for Automated Video Game Testing
Chengjia Wang, Lanling Tang, Ming Yuan +3
Testing MMORPGs (Massively Multiplayer Online Role-Playing Games) is a critical yet labor-intensive task in game development due to their complexity and frequent updating nature. T…
A.S.E: A Repository-Level Benchmark for Evaluating Security in AI-Generated Code
Keke Lian, Bin Wang, Lei Zhang +19
The increasing adoption of large language models (LLMs) in software engineering necessitates rigorous security evaluation of their generated code. However, existing benchmarks ofte…
Chimera: Harnessing Multi-Agent LLMs for Automatic Insider Threat Simulation
Jiongchi Yu, Xiaofei Xie, Qiang Hu +2
Insider threats pose a persistent and critical security risk, yet are notoriously difficult to detect in complex enterprise environments, where malicious actions are often hidden w…
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…
The Foundation Cracks: A Comprehensive Study on Bugs and Testing Practices in LLM Libraries
Weipeng Jiang, Xiaoyu Zhang, Xiaofei Xie +4
Large Language Model (LLM) libraries have emerged as the foundational infrastructure powering today's AI revolution, serving as the backbone for LLM deployment, inference optimizat…
CAShift: Benchmarking Log-Based Cloud Attack Detection under Normality Shift
Jiongchi Yu, Xiaofei Xie, Qiang Hu +6
With the rapid advancement of cloud-native computing, securing cloud environments has become an important task. Log-based Anomaly Detection (LAD) is the most representative techniq…