Pith Number
pith:7O3ZY7ZA
pith:2024:7O3ZY7ZAK3VGJ32Z4MA6NA5MLC
not attested
not anchored
not stored
refs pending
Learning with Noisy Ground Truth: From 2D Classification to 3D Reconstruction
arxiv:2406.15982 v1 · 2024-06-23 · cs.CV · cs.AI · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{7O3ZY7ZAK3VGJ32Z4MA6NA5MLC}
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
· sign in to
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 | 2026-07-05T08:35:51.473909Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
fbb79c7f2056ea64ef59e301e683ac58a8e3dd1a4e0f72d076cf3f6291d86501
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/7O3ZY7ZAK3VGJ32Z4MA6NA5MLC \
| 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: fbb79c7f2056ea64ef59e301e683ac58a8e3dd1a4e0f72d076cf3f6291d86501
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "18008395aa9b088404c7d0ab6bec6e2cd8c48f535ba5bcdd2094c864d20f3c92",
"cross_cats_sorted": [
"cs.AI",
"cs.LG"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2024-06-23T02:21:48Z",
"title_canon_sha256": "7d38e7c1f1e38b3ab68951779f72750d35c8aa5e2d863d223aa624fb7580de6c"
},
"schema_version": "1.0",
"source": {
"id": "2406.15982",
"kind": "arxiv",
"version": 1
}
}