most citedLightKG: Efficient Knowledge-Aware Recommendations with Simplified GNN Architecture

9 citations · 9 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2026

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…

cs.MM2026

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…

cs.IR2026

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…

cs.IR2026

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…

cs.MM2025

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…

cs.HC2025

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…