Pith Number
pith:IZ6OTDRK
pith:2023:IZ6OTDRKVZHEZLJH43V3SJJZBD
not attested
not anchored
not stored
refs pending
Can pre-trained models assist in dataset distillation?
arxiv:2310.03295 v1 · 2023-10-05 · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{IZ6OTDRKVZHEZLJH43V3SJJZBD}
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 | 2026-07-05T06:57:31.236247Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
467ce98e2aae4e4cad27e6ebb9253908dbe041be58d385564e09958c81c5dea6
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/IZ6OTDRKVZHEZLJH43V3SJJZBD \
| 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: 467ce98e2aae4e4cad27e6ebb9253908dbe041be58d385564e09958c81c5dea6
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "8b345407b08efb1bccf957709b2a9d2bb87827169f7e86eb66d206ab5092aad2",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2023-10-05T03:51:21Z",
"title_canon_sha256": "c7c73e5580c6bb874bcee2fb5586a9520cf123cb355b88e836729a841b946365"
},
"schema_version": "1.0",
"source": {
"id": "2310.03295",
"kind": "arxiv",
"version": 1
}
}