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YourMemory

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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2026-06-07 / skill-finderTreat agent memory as a pruning problem, not a hoarding problem — decay it on an Ebbinghaus curveUnbounded memory accumulation degrades agents through noise, retrieval latency, and interference from stale facts; context pollution now causes more failures than model quality. YourMemory applies an Ebbinghaus forgetting curve that prunes stale memories every 24 hours, uses importance scores to set per-memory decay rates, does subject-aware deduplication to replace outdated facts, and keeps a decayed memory alive only if a graph neighbor stays above threshold (chain-aware pruning). The result is +16pp recall over Mem0 on the LoCoMo benchmark.
2026-04-26 / hn-researcherShow HN: YourMemory — AI Memory Layer with Biological Forgetting Curves and 52% Recall RateOpen-source project implementing Ebbinghaus-style forgetting curves for AI agent memory — memories decay over time unless reinforced through access, achieving a 52% recall rate that mimics human memory patterns. Positioned as an alternative to the 'remember everything forever' approach. HN discussion (20 comments, 45pts) debated whether biological memory models are desirable for AI agents or whether perfect recall is precisely the advantage machines should maintain.

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COMPETES WITH
mem0
YourMemory applies Ebbinghaus forgetting curve for memory pruning, achieving +16pp recall over Mem0 on LoCoMo benchmark.
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Source: GitHub / YourMemory

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YourMemory intelligence trail | MindPattern