1 citations · 1 across the 8 of their papers we have counts for
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Graph Coarsening via Supervised Granular-Ball for Scalable Graph Neural Network Training
Shuyin Xia, Xinjun Ma, Zhiyuan Liu +3
Graph Neural Networks (GNNs) have demonstrated significant achievements in processing graph data, yet scalability remains a substantial challenge. To address this, numerous graph c…
Multi-Granularity Open Intent Classification via Adaptive Granular-Ball Decision Boundary
Yanhua Li, Xiaocao Ouyang, Chaofan Pan +6
Open intent classification is critical for the development of dialogue systems, aiming to accurately classify known intents into their corresponding classes while identifying unkno…
PA-LLaVA: A Large Language-Vision Assistant for Human Pathology Image Understanding
Dawei Dai, Yuanhui Zhang, Long Xu +4
The previous advancements in pathology image understanding primarily involved developing models tailored to specific tasks. Recent studies has demonstrated that the large vision-la…
A robust three-way classifier with shadowed granular-balls based on justifiable granularity
Jie Yang, Lingyun Xiaodiao, Guoyin Wang +4
The granular-ball (GB)-based classifier introduced by Xia, exhibits adaptability in creating coarse-grained information granules for input, thereby enhancing its generality and fle…