pith:WVCPJ7DF
Borrowed Geometry: Cross-Distribution Head-Importance Fingerprints of Frozen Pretrained Gemma 4 31B
Frozen text-pretrained transformer weights transfer to robotic and memory tasks through a thin trainable interface without modifying the core model.
arxiv:2605.00333 v2 · 2026-05-01 · cs.LG · cs.CL
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\usepackage{pith}
\pithnumber{WVCPJ7DFE2VY4HPZU2G4CROND4}
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Claims
Frozen Gemma 4 31B weights pretrained exclusively on text tokens, unmodified, transfer across modality boundaries through a thin trainable interface.
That the geometry captured by text-only pretraining remains useful and transferable to non-text modalities without any modification to the core frozen weights.
Frozen text-pretrained transformer weights transfer across modalities through a thin interface, achieving SOTA on a robotic task and parity on decision-making with far fewer trainable parameters.
Receipt and verification
| First computed | 2026-05-20T01:05:14.867261Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
b544f4fc6526ab8e1df9a68dc145cd1f2b01c9cf294eae838dc1cda66159d5a7
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/WVCPJ7DFE2VY4HPZU2G4CROND4 \
| 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: b544f4fc6526ab8e1df9a68dc145cd1f2b01c9cf294eae838dc1cda66159d5a7
Canonical record JSON
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"license": "http://creativecommons.org/licenses/by/4.0/",
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