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IceBerg Benchmark Exposes Evaluation Pitfalls In Vector Retrieval Algorithms

IceBerg Benchmark Exposes Evaluation Pitfalls In Vector Retrieval Algorithms


Vector retrieval educated Fu Cong, together with a evaluation workforce from Zhejiang Faculty, has launched IceBerg, a model new benchmark designed to disclose necessary gaps between commonplace vector retrieval evaluations and precise downstream job effectivity.

The analysis highlights that in functions equal to RAG, builders sometimes default to algorithms like HNSW. However, when examined in opposition to precise semantic duties, HNSW shouldn’t be continually the optimum choice.

IceBerg presents a multimodal benchmark and an computerized algorithm selection framework to help builders choose acceptable retrieval algorithms. The workforce argues that evaluation ought to focus additional on precise downstream effectivity.

Provide:liangziwei

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