While recent multimodal recommender systems have demonstrated the effectiveness of incorporating visual and textual information to improve downstream performance, most existing methods rely on static modality fusion, assuming that the relative importance of textual and visual signals remains stable across recommendatio...
Honghao Fu, Jiacheng Chen, Man-Xi Lin et al.· 0 citations
Pailitao-MMSearch is presented, one native e-commerce multimodal search foundation model designed to bridge this gap, and introduces three key innovations:HybSID (Hybrid Semantic ID);(2)a two-stage continual pre-training strategy; and (3)a hybrid reasoning post-training pipeline.
Xiaohan Ye, Xu Chen, Zi-Han Gong et al.· arXiv.org· 0 citations
RippleNet is proposed, an AI-generated image detection framework based on local differential signals that adaptively identifies forgery-sensitive regions and constructs multi-directional, multi-scale differential representations within local neighborhoods, explicitly characterizing anomalous patterns in neighborhood st...
Jia-Zhen Yang, Ruijin Jin, Junjun Zheng et al.· 0 citations
RecGPT-V3 is presented, a stateful, hybrid-modal recommender that reasons over natural language for open-world knowledge and Semantic IDs (SIDs) for concrete item grounding and achieves consistent gains in large-scale online A/B tests.
