pith:HSPOK5VN
Graph Memory Transformer (GMT)
A learned graph of memory centroids can replace the feed-forward sublayer in a decoder-only transformer.
arxiv:2604.23862 v2 · 2026-04-26 · cs.LG · cs.AI · cs.CL
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\pithnumber{HSPOK5VN2LCBPFIJXBTSX45JCR}
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Claims
The base GMT v7 model trains stably and exposes centroid usage, transition structure, and source-to-target movement as directly inspectable quantities of the forward computation. It remains behind the larger dense baseline in validation loss and perplexity (3.5995/36.58 vs. 3.2903/26.85), while showing close zero-shot benchmark behavior under the evaluated setting.
That gravitational source routing plus token-conditioned target selection plus gated displacement readout can functionally substitute for the dense FFN transformation without requiring additional capacity or architectural changes outside the memory cell itself.
Graph Memory Transformer (GMT) swaps dense FFN sublayers for a graph of 128 centroids and a learned 128x128 transition matrix per block, yielding a 82M-parameter decoder-only LM that trains stably but trails a 103M dense baseline in perplexity.
Receipt and verification
| First computed | 2026-05-28T02:04:48.216382Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
3c9ee576add2c4179509b8672bf3a9145e2eddb17055a71cf5a98061cacbf45a
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/HSPOK5VN2LCBPFIJXBTSX45JCR \
| 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: 3c9ee576add2c4179509b8672bf3a9145e2eddb17055a71cf5a98061cacbf45a
Canonical record JSON
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