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cs.CV2024
CMOOD: Concept-based Multi-label OOD Detection
Zhendong Liu, Yi Nian, Yuehan Qin +4
How can models effectively detect out-of-distribution (OOD) samples in complex, multi-label settings without extensive retraining? Existing OOD detection methods struggle to captur…
cs.CV2024★ 1 cited
EIVEN: Efficient Implicit Attribute Value Extraction using Multimodal LLM
Henry Peng Zou, Gavin Heqing Yu, Ziwei Fan +5
In e-commerce, accurately extracting product attribute values from multimodal data is crucial for improving user experience and operational efficiency of retailers. However, previo…
cs.CV2024
ImplicitAVE: An Open-Source Dataset and Multimodal LLMs Benchmark for Implicit Attribute Value Extraction
Henry Peng Zou, Vinay Samuel, Yue Zhou +5
Existing datasets for attribute value extraction (AVE) predominantly focus on explicit attribute values while neglecting the implicit ones, lack product images, are often not publi…