Pith Number
pith:PEMU67Y4
pith:2026:PEMU67Y4RGTUY6OG7ODF4LUG27
not attested
not anchored
not stored
refs pending
GAP-MLLM: Geometry-Aligned Pre-training for Activating 3D Spatial Perception in Multimodal Large Language Models
arxiv:2603.16461 v2 · 2026-03-17 · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{PEMU67Y4RGTUY6OG7ODF4LUG27}
Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge
Record completeness
1
Bitcoin timestamp
2
Internet Archive
3
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4
Citations
5
Replications
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Portable graph bundle live · download bundle · merged
state
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.
Cited by
Receipt and verification
| First computed | 2026-07-21T01:21:43.687008Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
79194f7f1c89a74c79c6fb865e2e86d7d2f02d2676b323205c690c62440ac224
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/PEMU67Y4RGTUY6OG7ODF4LUG27 \
| 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: 79194f7f1c89a74c79c6fb865e2e86d7d2f02d2676b323205c690c62440ac224
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "5511290aa761860acc7f7fdf49c4c020e107a90f01c8704d629f8de8181a1b97",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2026-03-17T12:43:48Z",
"title_canon_sha256": "114337600b0042500afa3e6b4c119bef5a46f903b186c5b10b266fc91aef4f72"
},
"schema_version": "1.0",
"source": {
"id": "2603.16461",
"kind": "arxiv",
"version": 2
}
}