3 citations · 4 across the 2 of their papers we have counts for
3 papers
cs.AI2026
MAADBench: The Refreshable Paradigm for Anomaly Detection in Multi-Agent Systems
Lei Ma, Dennis Hofmann, Haowen Xu +4
Recent studies report that LLM-based multi-agent systems (MAS) fail at rates of 41%-87%, yet to our knowledge, no benchmark to date supports systematic anomaly detection (AD) for t…
cs.DB2025★ 1 cited
HARMONY: A Scalable Distributed Vector Database for High-Throughput Approximate Nearest Neighbor Search
Qian Xu, Feng Zhang, Chengxi Li +4
Approximate Nearest Neighbor Search (ANNS) is essential for various data-intensive applications, including recommendation systems, image retrieval, and machine learning. Scaling AN…
cs.LG2024★ 3 cited
UMGAD: Unsupervised Multiplex Graph Anomaly Detection
Xiang Li, Jianpeng Qi, Zhongying Zhao +4
Graph anomaly detection (GAD) is a critical task in graph machine learning, with the primary objective of identifying anomalous nodes that deviate significantly from the majority.…