Search Results for author:
Found 4 papers, 3 papers with code
Leveraging Multimodal Features and Item-level User Feedback for Bundle Construction
Specifically, we use self-attention modules to combine the multimodal and multi-item features, and then leverage both item- and bundle-level contrastive learning to enhance the representation learning, thus to counter the modality missing, noise, and sparsity problems.
INO at Factify 2: Structure Coherence based Multi-Modal Fact Verification
Therefore, we proposed a structure coherence-based multi-modal fact verification scheme to classify fake news.
BiSTNet: Semantic Image Prior Guided Bidirectional Temporal Feature Fusion for Deep Exemplar-based Video Colorization
To overcome this problem, we further develop a mixed expert block to extract semantic information for modeling the object boundaries of frames so that the semantic image prior can better guide the colorization process for better performance.
UA-FedRec: Untargeted Attack on Federated News Recommendation
Our study reveals a critical security issue in existing federated news recommendation systems and calls for research efforts to address the issue.
