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Many agent memory systems trail plain RAG on three long-context benchmarks

1 article1 sourcesince Oct 27Last article

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An arXiv paper (2610.34073) reports that many dedicated agent memory systems score below naive retrieval over raw history on LongMemEval, PersonaMem, and MINT-Eval, while costing much more.

The authors, as relayed by Elvis Saravia, split a memory system's value into a memory benefit, questions it answers that RAG misses, and a memory tax, questions RAG answers that the memory system gets wrong. Retrieving from raw history alongside memory and reranking both together reduced the tax, according to the paper.

Written by AI from the articles below · updated Oct 27, 11:41 AM ET

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Latest developmentOct 27, 11:11 AM ET
Plain RAG beats many agent memory systems on three benchmarks

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Oct 27
  1. elvisX
    Plain RAG beats many agent memory systems on three benchmarks

    AIA new arXiv paper finds many dedicated agent memory systems score below naive retrieval over raw history on LongMemEval, PersonaMem, and MINT-Eval, while costing more. The authors split a memory system's value into a memory benefit, questions it answers that RAG misses, and a memory tax, questions RAG answers that it gets wrong. Retrieving from raw history alongside memory and reranking both reduced the tax.

    Image from @omarsar0's post

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