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Found 4 papers, 2 papers with code
MADCluster: Model-agnostic Anomaly Detection with Self-supervised Clustering Network
In this paper, we propose MADCluster, a novel model-agnostic anomaly detection framework utilizing self-supervised clustering.
MAFA: Managing False Negatives for Vision-Language Pre-training
We consider a critical issue of false negatives in Vision-Language Pre-training (VLP), a challenge that arises from the inherent many-to-many correspondence of image-text pairs in large-scale web-crawled datasets.
Power Allocation for Device-to-Device Interference Channel Using Truncated Graph Transformers
Power control for the device-to-device interference channel with single-antenna transceivers has been widely analyzed with both model-based methods and learning-based approaches.
PU-EdgeFormer: Edge Transformer for Dense Prediction in Point Cloud Upsampling
We employ graph convolution using EdgeConv, which learns the local geometry and global structure of point cloud better than existing point-to-feature method.
