most citedMASKDROID: Robust Android Malware Detection with Masked Graph Representations

8 citations · 15 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CR20248 cited

MASKDROID: Robust Android Malware Detection with Masked Graph Representations

Jingnan Zheng, Jiaohao Liu, An Zhang +4

Android malware attacks have posed a severe threat to mobile users, necessitating a significant demand for the automated detection system. Among the various tools employed in malwa…

cs.CV2024

View Distribution Alignment with Progressive Adversarial Learning for UAV Visual Geo-Localization

Cuiwei Liu, Jiahao Liu, Huaijun Qiu +2

Unmanned Aerial Vehicle (UAV) visual geo-localization aims to match images of the same geographic target captured from different views, i.e., the UAV view and the satellite view. I…

cs.CL2023

Improving Input-label Mapping with Demonstration Replay for In-context Learning

Zhuocheng Gong, Jiahao Liu, Qifan Wang +4

In-context learning (ICL) is an emerging capability of large autoregressive language models where a few input-label demonstrations are appended to the input to enhance the model's…

cs.CL2023

Retrieval-based Knowledge Transfer: An Effective Approach for Extreme Large Language Model Compression

Jiduan Liu, Jiahao Liu, Qifan Wang +5

Large-scale pre-trained language models (LLMs) have demonstrated exceptional performance in various natural language processing (NLP) tasks. However, the massive size of these mode…

cs.IR2023

AutoSeqRec: Autoencoder for Efficient Sequential Recommendation

Sijia Liu, Jiahao Liu, Hansu Gu +4

Sequential recommendation demonstrates the capability to recommend items by modeling the sequential behavior of users. Traditional methods typically treat users as sequences of ite…

cs.IR20232 cited

Recommendation Unlearning via Matrix Correction

Jiahao Liu, Dongsheng Li, Hansu Gu +5

Recommender systems are important for providing personalized services to users, but the vast amount of collected user data has raised concerns about privacy (e.g., sensitive data),…