3 papers
cs.IR2026
A General Framework for Multimodal LLM-Based Multimedia Understanding in Large-Scale Recommendation Systems
Yiming Zhu, Xu Liu, Ziyun Xu +9
Conventional recommendation systems frequently fail to fully exploit the high-dimensional semantic signals inherent in multimedia content, thereby limiting the fidelity of user pre…
cs.IR2025
CTR-Driven Ad Text Generation via Online Feedback Preference Optimization
Yanda Chen, Zihui Ren, Qixiang Gao +5
Advertising text plays a critical role in determining click-through rates (CTR) in online advertising. Large Language Models (LLMs) offer significant efficiency advantages over man…
cs.IR2025
MIM: Multi-modal Content Interest Modeling Paradigm for User Behavior Modeling
Bencheng Yan, Si Chen, Shichang Jia +12
Click-Through Rate (CTR) prediction is a crucial task in recommendation systems, online searches, and advertising platforms, where accurately capturing users' real interests in con…