9 citations · 9 across the 8 of their papers we have counts for
8 papers
FashionStylist: An Expert Knowledge-enhanced Multimodal Dataset for Fashion Understanding
Kaidong Feng, Zhuoxuan Huang, Huizhong Guo +7
Fashion understanding requires both visual perception and expert-level reasoning about style, occasion, compatibility, and outfit rationale. However, existing fashion datasets rema…
Through Their Eyes: Fixation-aligned Tuning for Personalized User Emulation
Lingfeng Huang, Huizhong Guo, Tianjun Wei +2
Large language model (LLM) agents are increasingly deployed as scalable user simulators for recommender system evaluation. Yet existing simulators perceive recommendations through…
MMGRid: Navigating Temporal-aware and Cross-domain Generative Recommendation via Model Merging
Tianjun Wei, Enneng Yang, Yingpeng Du +3
Model merging (MM) offers an efficient mechanism for integrating multiple specialized models without access to original training data or costly retraining. While MM has demonstrate…
Think When Needed: Model-Aware Reasoning Routing for LLM-based Ranking
Huizhong Guo, Tianjun Wei, Dongxia Wang +4
Large language models (LLMs) are increasingly applied to ranking tasks in retrieval and recommendation. Although reasoning prompting can enhance ranking utility, our preliminary ex…
When Harmful Content Gets Camouflaged: Unveiling Perception Failure of LVLMs with CamHarmTI
Yanhui Li, Qi Zhou, Zhihong Xu +3
Large vision-language models (LVLMs) are increasingly used for tasks where detecting multimodal harmful content is crucial, such as online content moderation. However, real-world h…
Mirroring Users: Towards Building Preference-aligned User Simulator with User Feedback in Recommendation
Tianjun Wei, Huizhong Guo, Yingpeng Du +4
User simulation is increasingly vital to develop and evaluate recommender systems (RSs). While Large Language Models (LLMs) offer promising avenues to simulate user behavior, they…
LightKG: Efficient Knowledge-Aware Recommendations with Simplified GNN Architecture
Yanhui Li, Dongxia Wang, Zhu Sun +2
Recently, Graph Neural Networks (GNNs) have become the dominant approach for Knowledge Graph-aware Recommender Systems (KGRSs) due to their proven effectiveness. Building upon GNN-…
Enhancing New-item Fairness in Dynamic Recommender Systems
Huizhong Guo, Zhu Sun, Dongxia Wang +3
New-items play a crucial role in recommender systems (RSs) for delivering fresh and engaging user experiences. However, traditional methods struggle to effectively recommend new-it…