Pith Number
pith:QLLG5U2H
pith:2025:QLLG5U2HZXAJGGRAFYHEUM7RLV
not attested
not anchored
not stored
refs pending
Heterogeneity-aware Personalized Federated Learning via Adaptive Dual-Agent Reinforcement Learning
arxiv:2501.16966 v1 · 2025-01-28 · cs.LG · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{QLLG5U2HZXAJGGRAFYHEUM7RLV}
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
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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 | 2026-07-05T10:06:20.936671Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
82d66ed347cdc0931a202e0e4a33f15d50d1885579bf718e0ac98ab96cc8ca42
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/QLLG5U2HZXAJGGRAFYHEUM7RLV \
| 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: 82d66ed347cdc0931a202e0e4a33f15d50d1885579bf718e0ac98ab96cc8ca42
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "139f22c45004e07907fd76767637fc0d73dc44e38eaf171cc6c2002de94989e7",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.LG",
"submitted_at": "2025-01-28T14:08:57Z",
"title_canon_sha256": "93ac7cff580db376c006c9b824fa7f55208373b2b1d04dc9f62f620afaeca201"
},
"schema_version": "1.0",
"source": {
"id": "2501.16966",
"kind": "arxiv",
"version": 1
}
}