ATTRIBUTE-ENHANCED FINE-GRAINED MULTI-MODAL REPRESENTATION LEARNING

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Challenge:	Multimodal representation is crucial for E-commerce tasks such as identical product retrieval.
Approach:	They propose an approach which leverages the generative power of Multimodal Large Language Models to extract key attributes from product images and text and enhances representation learning through a two-stage training framework.
Outcome:	The proposed model achieves state-of-the-art on multiple downstream retrieval tasks, validating the effectiveness of harnessing generative models to advance fine-grained representation learning.

Papers with Attribute-Enhanced Fine-Grained Multi-Modal Representation Learning