Pith Number
pith:DKJ63YG7
pith:2025:DKJ63YG7O5WZM5D6D2RH54ESJH
not attested
not anchored
not stored
refs pending
Semi-Supervised Federated Learning via Dual Contrastive Learning and Soft Labeling for Intelligent Fault Diagnosis
arxiv:2507.14181 v1 · 2025-07-12 · cs.LG · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{DKJ63YG7O5WZM5D6D2RH54ESJH}
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 | 2026-07-05T11:39:30.332222Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
1a93ede0df776d96747e1ea27ef09249d48f1880ce6f8e6966c21354dd1d60b3
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/DKJ63YG7O5WZM5D6D2RH54ESJH \
| 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: 1a93ede0df776d96747e1ea27ef09249d48f1880ce6f8e6966c21354dd1d60b3
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "3a9a1f2acf7d0e6633dd1b2fcc1bb3b537a1035b7bbc00663f8408ea2c675973",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2025-07-12T10:54:23Z",
"title_canon_sha256": "1c15a7af00a8e676497b772893e1860e9e7d96bc96cc859cb8de9c6d21dc86c9"
},
"schema_version": "1.0",
"source": {
"id": "2507.14181",
"kind": "arxiv",
"version": 1
}
}