19 citations · 70 across the 32 of their papers we have counts for
11 papers · 1 filter
HVM-GraphRAG: Holistic-View Multimodal Graph Retrieval-Augmented Generation on Complex Document
Xin He, Yili Wang, Wenqi Fan +4
Question answering (QA) over complex documents requires models to retrieve and integrate evidence distributed across distant document regions and modalities. Multimodal GraphRAG pr…
CFALR: Collaborative Filtering-Augmented Large Language Model for Personalized Fashion Outfit Recommendation
Yujuan Ding, Junrong Liao, Yunshan Ma +4
Personalized outfit recommendation poses a significant challenge in e-commerce and social media platforms, requiring systems that balance user preferences with aesthetic compatibil…
ReRec: Reasoning-Augmented LLM-based Recommendation Assistant via Reinforcement Fine-tuning
Jiani Huang, Shijie Wang, Liangbo Ning +2
With the rise of LLMs, there is an increasing need for intelligent recommendation assistants that can handle complex queries and provide personalized, reasoning-driven recommendati…
WebRec: Enhancing LLM-based Recommendations with Attention-guided RAG from Web
Zihuai Zhao, Yujuan Ding, Wenqi Fan +1
Recommender systems play a vital role in alleviating information overload and enriching users' online experience. In the era of large language models (LLMs), LLM-based recommender…
Continuous-time Discrete-space Diffusion Model for Recommendation
Chengyi Liu, Xiao Chen, Shijie Wang +2
In the era of information explosion, Recommender Systems (RS) are essential for alleviating information overload and providing personalized user experiences. Recent advances in dif…
Investigating and Mitigating Stereotype-aware Unfairness in LLM-based Recommendations
Zihuai Zhao, Wenqi Fan, Yao Wu +1
Large Language Models (LLMs) have demonstrated unprecedented language understanding and reasoning capabilities to capture diverse user preferences and advance personalized recommen…
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…
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…
Knowledge Graph Retrieval-Augmented Generation for LLM-based Recommendation
Shijie Wang, Wenqi Fan, Yue Feng +4
Recommender systems have become increasingly vital in our daily lives, helping to alleviate the problem of information overload across various user-oriented online services. The em…
SSD4Rec: A Structured State Space Duality Model for Efficient Sequential Recommendation
Haohao Qu, Yifeng Zhang, Liangbo Ning +2
Sequential recommendation methods are crucial in modern recommender systems for their remarkable capability to understand a user's changing interests based on past interactions. Ho…
TokenRec: Learning to Tokenize ID for LLM-based Generative Recommendation
Haohao Qu, Wenqi Fan, Zihuai Zhao +1
There is a growing interest in utilizing large-scale language models (LLMs) to advance next-generation Recommender Systems (RecSys), driven by their outstanding language understand…