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EvoEmbedding: Evolvable Representations for Long-Context Retrieval and Agentic Memory

📄 Paper Trending (17⬆️): Existing embedding models are inherently static: they encode text segments in isolation, ignoring their surrounding context and temporal order. This paper introduces EvoEmbedding, a novel embedding model that generates evolvable representations for retrieval. It is tailored for long-context scenario...

Fuente: HuggingFace_Papers

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📄 Paper Trending (17⬆️): Existing embedding models are inherently static: they encode text segments in isolation, ignoring their surrounding context and temporal order. This paper introduces EvoEmbedding, a novel embedding model that generates evolvable representations for retrieval. It is tailored for long-context scenario...

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EvoEmbedding: Evolvable Representations for Long-Context Retrieval and Agentic Memory | ToolAI - StudioCentOS