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Paper · arXiv

When Does Selection Replace Extraction? A Pre-Registered Test of Agent Memory with a Typed Decision Model

Does conversational memory need LLM-extracted facts, or is selecting the right raw turns enough? Published results disagree. Extraction-based systems report gains from distilled facts. Recent studies find raw history with good ranking does as well, but disagree about whether ranking matters. We ran a pre-registered study on held-out LoCoMo conversations and LongMemEval. At a tight budget on LoCoMo, raw turns selected by a single call to Jev, a typed decision model, are non-inferior to an LLM-extraction memory (one-sided 95% bound -3.0 points against a -5-point margin). Blind human grading narrows the margin but does not change the result. Raw turns cost 3,061 times less to write, and the ...

AuthorsRishabh Sharma, Rishika Lall
Primary categorycs.AI
Published28 September 2026
Last updated at source28 September 2026
cs.AIcs.CLcs.IR
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