From the 1 of 8 linked papers with an AI index.
8 papers
When Models Meet Users: An Empirical Study of Perceptions of General LLMs and Multimodal LLMs on Hugging Face
Yujian Liu, Xiao Yu, Jacky Keung +3
The paper empirically examines user discussions on Hugging Face to understand how people perceive general-purpose and multimodal large language models, identifying key concerns suc…
Teaching Software Engineering with LLM and MCP Integration: From Classroom to Industry Practice
Kehui Chen, Jacky Keung, Weining Li +3
The rapid integration of Large Language Models (LLMs) and the Model Context Protocol (MCP) into industrial software engineering has created a pressing need to update software engin…
Understanding How Enterprises Adopt the Model Context Protocol for LLM-Driven Software Engineering
Kehui Chen, Yicheng Sun, Jacky Keung +2
Large Language Models (LLMs) are increasingly used in AI-based software engineering, but their limitations in complex task execution and multi-tool coordination have driven growing…
UniAda: Universal Adaptive Multi-objective Adversarial Attack for End-to-End Autonomous Driving Systems
Jingyu Zhang, Jacky Wai Keung, Yan Xiao +3
Adversarial attacks play a pivotal role in testing and improving the reliability of deep learning (DL) systems. Existing literature has demonstrated that subtle perturbations to th…
A Comprehensive Study of Bugs in Modern Distributed Deep Learning Systems
Xiaoxue Ma, Wanwei Zhan, Jiale Chen +3
In today's data-driven era, deep learning is vital for processing massive datasets, yet single-device training is constrained by computational and memory limits. Distributed deep l…
PerProb: Indirectly Evaluating Memorization in Large Language Models
Yihan Liao, Jacky Keung, Xiaoxue Ma +2
The rapid advancement of Large Language Models (LLMs) has been driven by extensive datasets that may contain sensitive information, raising serious privacy concerns. One notable th…