1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2025
Less is More: Efficient Black-box Attribution via Minimal Interpretable Subset Selection
Ruoyu Chen, Siyuan Liang, Jingzhi Li +4
To develop a trustworthy AI system, it is essential to understand its behavior using attribution methods, which aim to identify the input regions that most influence the model's de…
cs.CV2024★ 1 cited
Less is More: Fewer Interpretable Region via Submodular Subset Selection
Ruoyu Chen, Hua Zhang, Siyuan Liang +2
Image attribution algorithms aim to identify important regions that are highly relevant to model decisions. Although existing attribution solutions can effectively assign importanc…
cs.CV2017
Cascade one-vs-rest detection network for fine-grained recognition without part annotations
Long Chen, Junyu Dong, ShengKe Wang +4
Fine-grained recognition is a challenging task due to the small intra-category variances. Most of top-performing fine-grained recognition methods leverage parts of objects for bett…