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RegRet is presented, an LMM-based Region-level Retrieval framework that enhances the regional representations without compromising overall global retrieval performance and designs a multi-stage training pipeline that includes detailed localized captioning and regional contrastive learning tasks.
Compact models can now adapt to changing environments without sacrificing performance, achieving a Live-Stream QA score that surpasses even the strongest general LLMs.