16 citations · 23 across the 4 of their papers we have counts for
5 papers
Large Language Models for Network Intrusion Detection Systems: Foundations, Implementations, and Future Directions
Shuo Yang, Xinran Zheng, Xinchen Zhang +5
Large Language Models (LLMs) have revolutionized various fields with their exceptional capabilities in understanding, processing, and generating human-like text. This paper investi…
Federated Selective Aggregation for Knowledge Amalgamation
Donglin Xie, Ruonan Yu, Gongfan Fang +5
In this paper, we explore a new knowledge-amalgamation problem, termed Federated Selective Aggregation (FedSA). The goal of FedSA is to train a student model for a new task with th…
CADG: A Model Based on Cross Attention for Domain Generalization
Cheng Dai, Yingqiao Lin, Fan Li +2
In Domain Generalization (DG) tasks, models are trained by using only training data from the source domains to achieve generalization on an unseen target domain, this will suffer f…
Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data
Gongfan Fang, Yifan Bao, Jie Song +4
Knowledge distillation~(KD) aims to craft a compact student model that imitates the behavior of a pre-trained teacher in a target domain. Prior KD approaches, despite their gratify…
PIC-Net: Point Cloud and Image Collaboration Network for Large-Scale Place Recognition
Yuheng Lu, Fan Yang, Fangping Chen +1
Place recognition is one of the hot research fields in automation technology and is still an open issue, Camera and Lidar are two mainstream sensors used in this task, Camera-based…