2 papers
cs.DB2025
Global Hash Tables Strike Back! An Analysis of Parallel GROUP BY Aggregation
Daniel Xue, Ryan Marcus
Efficiently computing group aggregations (i.e., GROUP BY) on modern architectures is critical for analytic database systems. Hash-based approaches in today's engines predominantly…
cs.CV2025
NexViTAD: Few-shot Unsupervised Cross-Domain Defect Detection via Vision Foundation Models and Multi-Task Learning
Tianwei Mu, Feiyu Duan, Bo Zhou +2
This paper presents a novel few-shot cross-domain anomaly detection framework, Nexus Vision Transformer for Anomaly Detection (NexViTAD), based on vision foundation models, which e…