Pith Number
pith:CIDDNMOJ
pith:2022:CIDDNMOJ7Q5PCQ737CADWRCBGU
not attested
not anchored
not stored
refs pending
LASSIE: Learning Articulated Shapes from Sparse Image Ensemble via 3D Part Discovery
arxiv:2207.03434 v1 · 2022-07-07 · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{CIDDNMOJ7Q5PCQ737CADWRCBGU}
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 | 2026-07-05T04:38:22.190725Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
120636b1c9fc3af143fbf8803b4441350b5b4294dd7c6b9ea7edbdd417d642bd
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/CIDDNMOJ7Q5PCQ737CADWRCBGU \
| 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: 120636b1c9fc3af143fbf8803b4441350b5b4294dd7c6b9ea7edbdd417d642bd
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "442c737c8d59a3ad705f942d1b8398b6a6ff17c6e8bbc56554fe95785f885817",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.CV",
"submitted_at": "2022-07-07T17:00:07Z",
"title_canon_sha256": "e91671d42ca1ffa7b551e20b7be72ab1eb5cd542b152b7ae6a5253a677fb02a9"
},
"schema_version": "1.0",
"source": {
"id": "2207.03434",
"kind": "arxiv",
"version": 1
}
}