9 citations · 17 across the 16 of their papers we have counts for
16 papers
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…
Where Agent Frameworks Fall Short: Examining Functional Challenges and Usability Concerns
Xinxue Zhu, Yanzhou Mu, Xiaoyu Zhang +5
Large language model (LLM) agents are increasingly built on agent frameworks that provide reusable abstractions for workflow orchestration, state management, tool integration, and…
False Friends in the Shell: Unveiling the Emoticon Semantic Confusion in Large Language Models
Weipeng Jiang, Xiaoyu Zhang, Juan Zhai +3
Emoticons are widely used in digital communication to convey affective intent, yet their safety implications for Large Language Models (LLMs) remain largely unexplored. In this pap…
Mitigating Stylistic Biases of Machine Translation Systems via Monolingual Corpora Only
Xuanqi Gao, Weipeng Jiang, Juan Zhai +4
The advent of neural machine translation (NMT) has revolutionized cross-lingual communication, yet preserving stylistic nuances remains a significant challenge. While existing appr…
ASSURE: Metamorphic Testing for AI-powered Browser Extensions
Xuanqi Gao, Juan Zhai, Shiqing Ma +2
The integration of Large Language Models (LLMs) into browser extensions has revolutionized web browsing, enabling sophisticated functionalities like content summarization, intellig…
MCP-RADAR: A Multi-Dimensional Benchmark for Evaluating Tool Use Capabilities in Large Language Models
Xuanqi Gao, Siyi Xie, Juan Zhai +2
As Large Language Models (LLMs) evolve from passive text generators to active reasoning agents capable of interacting with external tools, the Model Context Protocol (MCP) has emer…
Exposing Product Bias in LLM Investment Recommendation
Yuhan Zhi, Xiaoyu Zhang, Longtian Wang +4
Large language models (LLMs), as a new generation of recommendation engines, possess powerful summarization and data analysis capabilities, surpassing traditional recommendation sy…
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…
The Invisible Hand: Unveiling Provider Bias in Large Language Models for Code Generation
Xiaoyu Zhang, Juan Zhai, Shiqing Ma +5
Large Language Models (LLMs) have emerged as the new recommendation engines, surpassing traditional methods in both capability and scope, particularly in code generation. In this p…
Speculative Coreset Selection for Task-Specific Fine-tuning
Xiaoyu Zhang, Juan Zhai, Shiqing Ma +4
Task-specific fine-tuning is essential for the deployment of large language models (LLMs), but it requires significant computational resources and time. Existing solutions have pro…
Efficient DNN-Powered Software with Fair Sparse Models
Xuanqi Gao, Weipeng Jiang, Juan Zhai +3
With the emergence of the Software 3.0 era, there is a growing trend of compressing and integrating large models into software systems, with significant societal implications. Regr…
CITADEL: Context Similarity Based Deep Learning Framework Bug Finding
Xiaoyu Zhang, Juan Zhai, Shiqing Ma +2
With the application of deep learning technology, tools of DL framework testing are in high demand. Existing DL framework testing tools have limited coverage of bug types. For exam…
From Effectiveness to Efficiency: Uncovering Linguistic Bias in Large Language Model-based Code Generation
Weipeng Jiang, Xuanqi Gao, Juan Zhai +4
Large Language Models (LLMs) have demonstrated promising capabilities for code generation. While existing benchmarks evaluate the correctness and efficiency of LLM-generated code,…
Your Large Language Model is Secretly a Fairness Proponent and You Should Prompt it Like One
Tianlin Li, Xiaoyu Zhang, Chao Du +5
The widespread adoption of large language models (LLMs) underscores the urgent need to ensure their fairness. However, LLMs frequently present dominant viewpoints while ignoring al…
DREAM: Debugging and Repairing AutoML Pipelines
Xiaoyu Zhang, Juan Zhai, Shiqing Ma +1
Deep Learning models have become an integrated component of modern software systems. In response to the challenge of model design, researchers proposed Automated Machine Learning (…
JailGuard: A Universal Detection Framework for LLM Prompt-based Attacks
Xiaoyu Zhang, Cen Zhang, Tianlin Li +7
The systems and software powered by Large Language Models (LLMs) and Multi-Modal LLMs (MLLMs) have played a critical role in numerous scenarios. However, current LLM systems are vu…