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4 papers
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…
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…
Vision Enhancing LLMs: Empowering Multimodal Knowledge Storage and Sharing in LLMs
Yunxin Li, Zhenyu Liu, Baotian Hu +4
Recent advancements in multimodal large language models (MLLMs) have achieved significant multimodal generation capabilities, akin to GPT-4. These models predominantly map visual i…
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…