Pith Number
pith:NUPJRV7L
pith:2026:NUPJRV7LUDRNQ5FRV3L5AEIUJV
not attested
not anchored
not stored
refs pending
MetricAnything: Scaling Metric Depth Pretraining with Noisy Heterogeneous Sources
arxiv:2601.22054 v2 · 2026-01-29 · cs.CV · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{NUPJRV7LUDRNQ5FRV3L5AEIUJV}
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.
Cited by
Receipt and verification
| First computed | 2026-07-07T01:16:05.013821Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
6d1e98d7eba0e2d874b1aed7d011144d7a801d96306612e527ec0067731d9406
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/NUPJRV7LUDRNQ5FRV3L5AEIUJV \
| 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: 6d1e98d7eba0e2d874b1aed7d011144d7a801d96306612e527ec0067731d9406
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "6297532d40b4d021959a5e43a918fbb33b6e8424d4a9ab72de2e197b707852b8",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.CV",
"submitted_at": "2026-01-29T17:52:41Z",
"title_canon_sha256": "406d01f57326811cf52ec1fd868139276afdc5b52e0c916718461ecf93f3cc76"
},
"schema_version": "1.0",
"source": {
"id": "2601.22054",
"kind": "arxiv",
"version": 2
}
}