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Greatest papers with code

Multimodal Joint Attribute Prediction and Value Extraction for E-commerce Product

EMNLP 2020 jd-aig/JAVE

We annotate a multimodal product attribute value dataset that contains 87, 194 instances, and the experimental results on this dataset demonstrate that explicitly modeling the relationship between attributes and values facilitates our method to establish the correspondence between them, and selectively utilizing visual product information is necessary for the task.

ATTRIBUTE VALUE EXTRACTION