7 papers
Well Begun is Half Done: Training-Free and Model-Agnostic Semantically Guaranteed User Representation Initialization for Multimodal Recommendation
Jinfeng Xu, Zheyu Chen, Shuo Yang +6
Recent advancements in multimodal recommendations, which leverage diverse modality information to mitigate data sparsity and improve recommendation accuracy, have gained significan…
OVG-HQ: Online Video Grounding with Hybrid-modal Queries
Runhao Zeng, Jiaqi Mao, Minghao Lai +5
Video grounding (VG) task focuses on locating specific moments in a video based on a query, usually in text form. However, traditional VG struggles with some scenarios like streami…
Enhancing Graph Collaborative Filtering with FourierKAN Feature Transformation
Jinfeng Xu, Zheyu Chen, Jinze Li +4
Graph Collaborative Filtering (GCF) has emerged as a dominant paradigm in modern recommendation systems, excelling at modeling complex user-item interactions and capturing high-ord…
NLGCL: Naturally Existing Neighbor Layers Graph Contrastive Learning for Recommendation
Jinfeng Xu, Zheyu Chen, Shuo Yang +5
Graph Neural Networks (GNNs) are widely used in collaborative filtering to capture high-order user-item relationships. To address the data sparsity problem in recommendation system…
COHESION: Composite Graph Convolutional Network with Dual-Stage Fusion for Multimodal Recommendation
Jinfeng Xu, Zheyu Chen, Wei Wang +3
Recent works in multimodal recommendations, which leverage diverse modal information to address data sparsity and enhance recommendation accuracy, have garnered considerable intere…
Deep Robust Reversible Watermarking
Jiale Chen, Wei Wang, Chongyang Shi +3
Robust Reversible Watermarking (RRW) enables perfect recovery of cover images and watermarks in lossless channels while ensuring robust watermark extraction in lossy channels. Exis…