Pith Number
pith:YC7QFPUK
pith:2025:YC7QFPUKCIKZCCPZLHNE3Q2FQG
not attested
not anchored
not stored
refs pending
Personalized Federated Fine-tuning for Heterogeneous Data: An Automatic Rank Learning Approach via Two-Level LoRA
arxiv:2503.03920 v1 · 2025-03-05 · cs.LG · cs.CL
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{YC7QFPUKCIKZCCPZLHNE3Q2FQG}
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 | 2026-07-05T10:25:24.319269Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
c0bf02be8a12159109f959da4dc345819ec839a8da6fc5a78b1097e9024dbcfb
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/YC7QFPUKCIKZCCPZLHNE3Q2FQG \
| 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: c0bf02be8a12159109f959da4dc345819ec839a8da6fc5a78b1097e9024dbcfb
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "4b6629e41cf6c7bd40b83bc480d65bd9af8b8bb536603e82af7fe716f5588c45",
"cross_cats_sorted": [
"cs.CL"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2025-03-05T21:41:03Z",
"title_canon_sha256": "03240b58b913f118dd9bea1dcb13d5cc6b343d40ff0590353d9448a91e6448b7"
},
"schema_version": "1.0",
"source": {
"id": "2503.03920",
"kind": "arxiv",
"version": 1
}
}