9 citations · 16 across the 18 of their papers we have counts for
19 papers
Reliability Testing of Medical Model Performance under Distributed Deployment
Yifei Wang, Xiaohan Zhang, Youtao Ding +4
Distributed inference has become an indispensable part of deploying medical models under practical latency, memory, and throughput constraints. Although modern frameworks improve s…
Not as Sweet by Another Name: An Empirical Study of Format Robustness in LLM Document Workflows
Xiaoyu Zhang, Xianyun Cheng, Tianlin Li +3
LLM-driven software systems are rapidly evolving from plain-text conversations to document-centric end-to-end workflows, where the same semantic content can be delivered in diverse…
Trusted Weights, Treacherous Optimizations? Optimization-Triggered Backdoor Attacks on LLMs
Yifei Wang, Tianlin Li, Xiaohan Zhang +3
Inference optimization aims to minimize the latency and resource consumption of LLM inference while preserving output quality, making large-scale deployment practical and cost-effe…
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…
Rethinking Technology Stack Selection with AI Coding Proficiency
Xiaoyu Zhang, Weipeng Jiang, Shiqing Ma +5
Large language models (LLMs) are now an integral part of software development workflows and are reshaping the whole process. However, existing technology selection methods mainly f…
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…
Software Development Life Cycle Perspective: A Survey of Benchmarks for Code Large Language Models and Agents
Kaixin Wang, Tianlin Li, Xiaoyu Zhang +7
Code large language models (CodeLLMs) and agents are increasingly being integrated into complex software engineering tasks spanning the entire Software Development Life Cycle (SDLC…
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…
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,…
Deep Learning Library Testing: Definition, Methods and Challenges
Xiaoyu Zhang, Weipeng Jiang, Chao Shen +4
In recent years, software systems powered by deep learning (DL) techniques have significantly facilitated people's lives in many aspects. As the backbone of these DL systems, vario…
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…