Pith Number

pith:H47YDJN6

pith:2026:H47YDJN6QLTUEOMDTYUCMZAPG6

not attested not anchored not stored refs pending

ZenBrain: A Neuroscience-Inspired 7-Layer Memory Architecture for Autonomous AI Systems

Alexander Bering

A 7-layer neuroscience-inspired memory system for AI reaches 91 percent of long-context oracle accuracy at 1/106th the token cost.

arxiv:2604.23878 v3 · 2026-04-26 · cs.AI · cs.LG

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3 Author claim open · sign in to claim

4 Citations open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

On LongMemEval-500, ZenBrain matches a long-context oracle's binary-judge accuracy to within 4.5 pp (47.7% vs. 52.2%; 91.3%) at 1/106th of the per-query token cost, and wins all 12 head-to-head answer-quality cells against Letta, Mem0, and A-Mem under Bonferroni correction.

C2weakest assumption

That the 15 neuroscience mechanisms translate directly into effective AI components without introducing hidden interactions or benchmark-specific artifacts, and that the 60-day stress ablations with 10 seeds fully isolate each mechanism's contribution.

C3one line summary

ZenBrain unifies 15 neuroscience mechanisms into a 7-layer memory system that achieves near-oracle long-context accuracy at 1/106th token cost and outperforms prior memory architectures in controlled comparisons.

Cited by

1 paper in Pith

MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents

Receipt and verification

First computed	2026-08-11T01:20:42.478004Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

3f3f81a5be82e74239839e2826640f37b9ef78fcb07785b0d2ae2fea5bfe1685

Aliases

arxiv: 2604.23878 · arxiv_version: 2604.23878v3 · doi: 10.48550/arxiv.2604.23878 · pith_short_12: H47YDJN6QLTU · pith_short_16: H47YDJN6QLTUEOMD · pith_short_8: H47YDJN6

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/H47YDJN6QLTUEOMDTYUCMZAPG6 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 3f3f81a5be82e74239839e2826640f37b9ef78fcb07785b0d2ae2fea5bfe1685

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "64a15dd32a35ce611e8255ddf4f18a94360c851b3b45b0f8c5e09b80b1997692",
    "cross_cats_sorted": [
      "cs.LG"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.AI",
    "submitted_at": "2026-04-26T20:39:19Z",
    "title_canon_sha256": "c2f94e3057661e312d8f27ecbf417ec5149b318e4c2d9ce5d9c91890b750c5fd"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.23878",
    "kind": "arxiv",
    "version": 3
  }
}