19 citations · 45 across the 10 of their papers we have counts for
6 papers · 1 filter
mKG-RAG: Leveraging Multimodal Knowledge Graphs in Retrieval-Augmented Generation for Knowledge-intensive VQA
Xu Yuan, Liangbo Ning, Qingqing Ye +2
Retrieval-Augmented Generation (RAG) has emerged as an effective paradigm for expanding the knowledge capacity of Multimodal Large Language Models (MLLMs) by incorporating external…
CheatAgent: Attacking LLM-Empowered Recommender Systems via LLM Agent
Liang-bo Ning, Shijie Wang, Wenqi Fan +4
Recently, Large Language Model (LLM)-empowered recommender systems (RecSys) have brought significant advances in personalized user experience and have attracted considerable attent…
Exploring Backdoor Attack and Defense for LLM-empowered Recommendations
Liangbo Ning, Wenqi Fan, Qing Li
The fusion of Large Language Models (LLMs) with recommender systems (RecSys) has dramatically advanced personalized recommendations and drawn extensive attention. Despite the impre…
Retrieval-Augmented Purifier for Robust LLM-Empowered Recommendation
Liangbo Ning, Wenqi Fan, Qing Li
Recently, Large Language Model (LLM)-empowered recommender systems have revolutionized personalized recommendation frameworks and attracted extensive attention. Despite the remarka…
A Survey of WebAgents: Towards Next-Generation AI Agents for Web Automation with Large Foundation Models
Liangbo Ning, Ziran Liang, Zhuohang Jiang +8
With the advancement of web techniques, they have significantly revolutionized various aspects of people's lives. Despite the importance of the web, many tasks performed on it are…
Towards Next-Generation Recommender Systems: A Benchmark for Personalized Recommendation Assistant with LLMs
Jiani Huang, Shijie Wang, Liang-bo Ning +4
Recommender systems (RecSys) are widely used across various modern digital platforms and have garnered significant attention. Traditional recommender systems usually focus only on…