ReCQR: Incorporating conversational query rewriting to improve Multimodal Image Retrieval
📰 ArXiv cs.AI
ReCQR improves multimodal image retrieval by incorporating conversational query rewriting to handle unclear user expressions
Action Steps
- Identify the limitations of existing image retrievers in handling long texts and unclear user expressions
- Construct a dedicated multi-turn dialogue query rewriting dataset to support conversational query rewriting
- Develop and train a model that incorporates conversational query rewriting to improve image retrieval accuracy
- Evaluate the performance of the ReCQR model on a benchmark dataset and compare it to existing image retrievers
Who Needs to Know This
AI engineers and researchers on a team can benefit from this approach to improve the accuracy of image retrieval models, while product managers can leverage this technology to enhance user experience
Key Insight
💡 Incorporating conversational query rewriting can significantly improve the accuracy of multimodal image retrieval models
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📸 Improve image retrieval with ReCQR, a conversational query rewriting approach!
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