MMKG-RAG
What it is
A Retrieval-Augmented Generation (RAG) system that integrates Multi-Modal Knowledge Graphs (MMKG) to handle complex cross-modal queries. It captures rich semantic relationships across different types of data (text, images, etc.) to improve reasoning and retrieval accuracy.
The problem it solves
Conventional RAG systems often struggle with complex cross-modal reasoning and lack the ability to capture deep semantic links between different data modalities.
What you could use it for
- Multi-modal question answering (e.g., querying across text and images)
- Cross-modal information retrieval
- Reasoning over complex datasets with mixed media content
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Summary written by an AI model from the source; check the source before you rely on it.