Pith Number
pith:IRQ2PZQX
pith:2021:IRQ2PZQXVXLLAU5GF4HDPGIUNH
not attested
not anchored
not stored
refs pending
Are Large-scale Datasets Necessary for Self-Supervised Pre-training?
arxiv:2112.10740 v1 · 2021-12-20 · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{IRQ2PZQXVXLLAU5GF4HDPGIUNH}
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.
Cited by
Receipt and verification
| First computed | 2026-07-05T03:42:18.460230Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
4461a7e617add6b053a62f0e37991469f1f9527879baa2f01d68a667a484adc7
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/IRQ2PZQXVXLLAU5GF4HDPGIUNH \
| 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: 4461a7e617add6b053a62f0e37991469f1f9527879baa2f01d68a667a484adc7
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "0f88c67538368c059e43ca4b9d5494694640001ce84574860b3fd474349ce47a",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.CV",
"submitted_at": "2021-12-20T18:41:32Z",
"title_canon_sha256": "d5c94670e7a42de25ad754bd4990233d7e9d962205af2ca971a647ec1c52c8b2"
},
"schema_version": "1.0",
"source": {
"id": "2112.10740",
"kind": "arxiv",
"version": 1
}
}