Pith Number
pith:23VQDF27
pith:2026:23VQDF27EENBHLZSMYRSUJI6XL
not attested
not anchored
not stored
refs pending
MINCE: Shrinking LLM Evaluation Datasets via Few-Model Monte Carlo Calibration
arxiv:2606.22826 v1 · 2026-06-22 · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{23VQDF27EENBHLZSMYRSUJI6XL}
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 | 2026-06-23T02:14:00.494625Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
d6eb01975f211a13af3266232a251ebae106616021b140642963b10eba0c45ef
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/23VQDF27EENBHLZSMYRSUJI6XL \
| 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: d6eb01975f211a13af3266232a251ebae106616021b140642963b10eba0c45ef
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "bd14a4100f896f857b132e87cb9465ac6734eb34ef0eba6f6853dea376896798",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.AI",
"submitted_at": "2026-06-22T04:08:25Z",
"title_canon_sha256": "81e8a0ff45161b82033a7fa7788075c5b89126879a08f05c36f587d72c58c234"
},
"schema_version": "1.0",
"source": {
"id": "2606.22826",
"kind": "arxiv",
"version": 1
}
}