8 papers
Detecting Backdoors in Object Detection via Pre-NMS Prediction Distribution Shift
Longtian Wang, Zhengyu Zhao, Chenhao Lin +5
Object detection models deployed in safety-critical applications remain vulnerable to backdoor attacks that cause targeted misbehaviors when a hidden trigger is present. Existing d…
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…
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…
Selection-Based Vulnerabilities: Clean-Label Backdoor Attacks in Active Learning
Yuhan Zhi, Longtian Wang, Xiaofei Xie +3
Active learning(AL), which serves as the representative label-efficient learning paradigm, has been widely applied in resource-constrained scenarios. The achievement of AL is attri…
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…
TokenProber: Jailbreaking Text-to-image Models via Fine-grained Word Impact Analysis
Longtian Wang, Xiaofei Xie, Tianlin Li +2
Text-to-image (T2I) models have significantly advanced in producing high-quality images. However, such models have the ability to generate images containing not-safe-for-work (NSFW…
Benchmarking and Revisiting Code Generation Assessment: A Mutation-Based Approach
Longtian Wang, Tianlin Li, Xiaofei Xie +3
Code Large Language Models (CLLMs) have exhibited outstanding performance in program synthesis, attracting the focus of the research community. The evaluation of CLLM's program syn…
Holistic Audit Dataset Generation for LLM Unlearning via Knowledge Graph Traversal and Redundancy Removal
Weipeng Jiang, Juan Zhai, Shiqing Ma +4
In recent years, Large Language Models (LLMs) have faced increasing demands to selectively remove sensitive information, protect privacy, and comply with copyright regulations thro…