38 citations · 163 across the 25 of their papers we have counts for
6 papers · 1 filter
When Deepfake Detection Meets Graph Neural Network:a Unified and Lightweight Learning Framework
Haoyu Liu, Chaoyu Gong, Mengke He +3
The proliferation of generative video models has made detecting AI-generated and manipulated videos an urgent challenge. Existing detection approaches often fail to generalize acro…
[Extended Version] ArceKV: Towards Workload-driven LSM-compactions for Key-Value Store Under Dynamic Workloads
Junfeng Liu, Haoxuan Xie, Siqiang Luo
Key-value stores underpin a wide range of applications due to their simplicity and efficiency. Log-Structured Merge Trees (LSM-trees) dominate as their underlying structure, excell…
How to Grow an LSM-tree? Towards Bridging the Gap Between Theory and Practice
Dingheng Mo, Siqiang Luo, Stratos Idreos
LSM-tree based key-value stores are widely adopted as the data storage backend in modern big data applications. The LSM-tree grows with data ingestion, by either adding levels with…
Finding Near-Optimal Maximum Set of Disjoint -Cliques in Real-World Social Networks
Wenqing Lin, Xin Chen, Haoxuan Xie +2
A -clique is a dense graph, consisting of fully-connected nodes, that finds numerous applications, such as community detection and network analysis. In this paper, we study…
Aster: Enhancing LSM-structures for Scalable Graph Database
Dingheng Mo, Junfeng Liu, Fan Wang +1
There is a proliferation of applications requiring the management of large-scale, evolving graphs under workloads with intensive graph updates and lookups. Driven by this challenge…
Are Joins over LSM-Trees Ready? Take RocksDB as an Example
Weiping Yu, Fan Wang, Xuwei Zhang +1
LSM-tree-based data stores are widely adopted in industries for their excellent performance. As data scales increase, disk-based join operations become indispensable yet costly for…