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EvalMem: An Operation-Level Diagnostic Framework for Long-Term Memory Systems

Long-horizon interactions with LLM-based assistants require memory systems that preserve and update user states, preferences, and interaction…

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Why am I seeing this Ranked on source trust — arXiv

It ranks mainly on source trust: arXiv is the most reliable outlet we track on this subject, and is the only one on the story so far.

Link-outLink-out, because it did not clear the bar for a write-up. Link-out means we point at the publisher and say nothing of our own.

Blended score 0.546 — every figure below is computed, none of it is editorial.
FactorWeightScore ContributionWhere it came from
Corroboration 0.35 0.39 +0.135 25% 1 independent org on the story. Tier-3 aggregators never corroborate — they can show something is circulating, never that it is true.
Source trustleads 0.25 0.85 +0.212 39% arXiv is the highest-trust source on this story and is first-party — the organisation announcing its own news. Trust is taken from the best source, not averaged.
Pickup rate 0.20 0.00 +0.000 0% One counted organisation, so there is no spread to measure — nothing has picked this up to set a rate.
Freshness 0.20 0.99 +0.198 36% Halves every 10 hours from the newest item on the story. This is the only factor that rewards a story for nothing more than being recent.

Corroboration counts distinct organisations, once each, and only from tiers 1 and 2. Freshness halves every 10 hours, so this ranking is a snapshot and will differ at the next build.

Read the full article at Arxiv →

What happened

Long-horizon interactions with LLM-based assistants require memory systems that preserve and update user states, preferences, and interaction histories. Existing evaluations report end-to-end QA accuracy and cannot determine whether errors arise from encoding, retrieval, or generation. We introduce EvalMem, an operation-level diagnostic framework with three parallel Examiners. For each query, the Encoding Examiner checks whether the target fact is stored, the Retrieval Examiner assesses whether the native retriever returns usable evidence, and the Generation Examiner tests whether the model can answer from oracle evidence. Their outputs form fine-grained multi-label defect codes.

1independent orgs
25story score
0velocity
85source trust
9passes seen

How this story arrived

Ordered by when each source was first observed, which is what the velocity figure is computed from. Publishers backdate; observed order does not.

  1. 01 Arxivfirst-party first seen EvalMem: An Operation-Level Diagnostic Framework for Long-Term Memory Systems

Overclock clusters coverage from independent sources and grades it automatically. The figures above are computed, not editorial. This page summarises and links to reporting by the outlets named — follow the links for the original work.