Pith Number
pith:X7B2RKPJ
pith:2024:X7B2RKPJIXZKI3R422YEYNFMFL
not attested
not anchored
not stored
refs pending
Do LLMs Understand Visual Anomalies? Uncovering LLM's Capabilities in Zero-shot Anomaly Detection
arxiv:2404.09654 v3 · 2024-04-15 · cs.CV · cs.MM
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{X7B2RKPJIXZKI3R422YEYNFMFL}
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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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.
Cited by
Receipt and verification
| First computed | 2026-07-05T10:45:07.338912Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
bfc3a8a9e945f2a46e3cd6b04c34ac2ae1c3edbcf9f1a0398967128c1eb8f7cc
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/X7B2RKPJIXZKI3R422YEYNFMFL \
| 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: bfc3a8a9e945f2a46e3cd6b04c34ac2ae1c3edbcf9f1a0398967128c1eb8f7cc
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "7b7801a7d859cefe4f7ddf7093c1613dc67c4567b25e68d4c634d2c1667ecc4b",
"cross_cats_sorted": [
"cs.MM"
],
"license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
"primary_cat": "cs.CV",
"submitted_at": "2024-04-15T10:42:22Z",
"title_canon_sha256": "27969c7b9efbbac34dba12837ef6ebdf5600691297ed400ff47589f51cb1b36b"
},
"schema_version": "1.0",
"source": {
"id": "2404.09654",
"kind": "arxiv",
"version": 3
}
}