Core Idea - Contextualized chunk embedding models, such as voyage-context-3, process entire documents to embed chunks, leading to document-aware embeddings [1] - This approach enables semantically aware retrieval in Retrieval-Augmented Generation (RAG) systems [1] Technology - Voyage-context-3 is highlighted as an example of a contextualized chunk embedding model [1] - The method contrasts with producing independent chunk embeddings [1] Collaboration - The MongoDB team is acknowledged for their collaboration on this topic [1]

Despite tuning and balancing tradeoffs, the final chunk embeddings are generated independently with no interaction with each other.This isn't true with real-world docs, which have long-range dependencies.Check this 👇 https://t.co/3pydkHDNCN ...