Pith Number
pith:IM64NQXJ
pith:2025:IM64NQXJNLMRTULDU5XTYLYNKP
not attested
not anchored
not stored
refs pending
LMM-Det: Make Large Multimodal Models Excel in Object Detection
arxiv:2507.18300 v1 · 2025-07-24 · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{IM64NQXJNLMRTULDU5XTYLYNKP}
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
✓
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 | 2026-07-05T11:42:45.605053Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
433dc6c2e96ad919d163a76f3c2f0d53e1cc52226fcae93b2d7523af86a90b3a
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/IM64NQXJNLMRTULDU5XTYLYNKP \
| 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: 433dc6c2e96ad919d163a76f3c2f0d53e1cc52226fcae93b2d7523af86a90b3a
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "aea404da0feff786ea5de9197b412b059851b2bf532280d306db738063638a8e",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2025-07-24T11:05:24Z",
"title_canon_sha256": "32e4da814c5bd7970ef0e029b83064f779040f6246ca1f31be6b3a1930ab095d"
},
"schema_version": "1.0",
"source": {
"id": "2507.18300",
"kind": "arxiv",
"version": 1
}
}