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Bridging the semantic gap between images and text can dramatically enhance multimodal RAG performance, as shown by our novel Context-Enhanced MMKG framework.
A single checkpoint can now adapt to any model size, streamlining the deployment of elastic retrieval systems and achieving faster performance without sacrificing quality.
Mid-tier LLMs outperform their stronger counterparts in harness self-evolution, challenging assumptions about model capability and adaptability.
