29 citations · 31 across the 14 of their papers we have counts for
8 papers · 1 filter
Post-hoc Provider Fairness Adaptation via Hierarchical Exposure Alignment
Jingzhi Li, Zhiyong Cheng, Richang Hong +1
Provider exposure fairness is crucial for sustaining a healthy content ecosystem and preventing monopolization in recommender systems. Yet, most existing methods either incorporate…
A Survey on Generative Recommendation: Data, Model, and Tasks
Min Hou, Le Wu, Yuxin Liao +6
Recommender systems serve as foundational infrastructure in modern information ecosystems, helping users navigate digital content and discover items aligned with their preferences.…
I-MRec: Invariant Learning with Information Bottleneck for Incomplete Modality Recommendation
Huilin Chen, Miaomiao Cai, Fan Liu +3
Multimodal recommender systems (MRS) improve recommendation performance by integrating complementary semantic information from multiple modalities. However, the assumption of compl…
Invariance Matters: Empowering Social Recommendation via Graph Invariant Learning
Yonghui Yang, Le Wu, Yuxin Liao +4
Graph-based social recommendation systems have shown significant promise in enhancing recommendation performance, particularly in addressing the issue of data sparsity in user beha…
RecCocktail: A Generalizable and Efficient Framework for LLM-Based Recommendation
Min Hou, Chenxi Bai, Le Wu +6
Large Language Models (LLMs) have achieved remarkable success in recent years, owing to their impressive generalization capabilities and rich world knowledge. To capitalize on the…
Graph Bottlenecked Social Recommendation
Yonghui Yang, Le Wu, Zihan Wang +3
With the emergence of social networks, social recommendation has become an essential technique for personalized services. Recently, graph-based social recommendations have shown pr…
Double Correction Framework for Denoising Recommendation
Zhuangzhuang He, Yifan Wang, Yonghui Yang +6
As its availability and generality in online services, implicit feedback is more commonly used in recommender systems. However, implicit feedback usually presents noisy samples in…
Multimodality Invariant Learning for Multimedia-Based New Item Recommendation
Haoyue Bai, Le Wu, Min Hou +5
Multimedia-based recommendation provides personalized item suggestions by learning the content preferences of users. With the proliferation of digital devices and APPs, a huge numb…