Pith Number
pith:H5NVLYCF
pith:2026:H5NVLYCFCCBX4C64IDFZB4NGWO
not attested
not anchored
not stored
refs pending
Efficient Spatio-Temporal Grounding with Multimodal Large Models via Second-Level Tracking and RL Verification
arxiv:2606.29023 v1 · 2026-06-27 · cs.CV · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{H5NVLYCFCCBX4C64IDFZB4NGWO}
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
Author claim
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claim
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.
Receipt and verification
| First computed | 2026-06-30T01:17:49.793883Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
3f5b55e04510837e0bdc40cb90f1a6b3af26451129b12d535bdaf8ac493c56da
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/H5NVLYCFCCBX4C64IDFZB4NGWO \
| 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: 3f5b55e04510837e0bdc40cb90f1a6b3af26451129b12d535bdaf8ac493c56da
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "79430a4179e9bd5ba7d85a154a8f4ec9f4f8ceeb4adbeadfd6420685a54ab76f",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.CV",
"submitted_at": "2026-06-27T17:42:32Z",
"title_canon_sha256": "efcdb4546b3afb1f9aef834e56baa5bd893abbcd4fceed38377cd960772b2e4f"
},
"schema_version": "1.0",
"source": {
"id": "2606.29023",
"kind": "arxiv",
"version": 1
}
}