3 citations · 3 across the 9 of their papers we have counts for
5 papers · 1 filter
What Was Once Learned May Need to Be Unlearned: Machine Unlearning for Deprecated API Knowledge in Large Language Models
Jin Liu, Yanzhong He, Guancheng Lin +4
Large language models (LLMs) for code completion may generate deprecated APIs because their pre-training corpora contain code from historical library versions. Existing approaches…
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…
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
Large language models (LLMs) have rapidly evolved from general-purpose systems to multimodal models capable of processing text, images, and audio. As both general-purpose LLMs (GLL…