Amazon introduces FEB-30 benchmark testing agent memory stores against known facts
Overview
Amazon researchers introduce FEB-30, a benchmark of 30 scripted fact histories turned into 147 documents, so the correct memory state is known after each document.
Amazon says that on a memory system built like Mem0 and Hindsight, stored facts and QA scores differed by 16.8 points on average. The benchmark also found that pass/fail verdicts disagreed on 21% of fact histories, and the system chose the right memory action only 20.1% of the time.
The paper argues that QA scores alone miss broken memory stores, because the benchmark checks the stored facts directly against ground truth.
Written by AI from the articles below · updated Oct 19, 2:06 AM ET
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Rohan Paul@rohanpaul_aiXAmazon paper finds agent memory benchmarks miss broken memory storesAIAmazon researchers built FEB-30, a benchmark of 30 fact-evolution trajectories with known ground truth, to test agent memory directly. On a memory system built like Mem0 and Hindsight, stored facts and QA scores differed by 16.8 points on average. Pass/fail verdicts disagreed on 21% of fact histories, and the system chose the right memory action only 20.1% of the time.

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