Pith Number
pith:J7LO67KL
pith:2025:J7LO67KLPCWF2NPUXPGR65XBJ2
not attested
not anchored
not stored
refs pending
A Multi-Task Learning Approach to Linear Multivariate Forecasting
arxiv:2502.03571 v2 · 2025-02-05 · cs.LG · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{J7LO67KLPCWF2NPUXPGR65XBJ2}
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 | 2026-07-05T10:31:53.759030Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
4fd6ef7d4b78ac5d35f4bbcd1f76e14e96fe4955c7f3c8c02354428ee177c152
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/J7LO67KLPCWF2NPUXPGR65XBJ2 \
| 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: 4fd6ef7d4b78ac5d35f4bbcd1f76e14e96fe4955c7f3c8c02354428ee177c152
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "391af24d44f7d461c088e77794bde39db07fa7fe53671357533d07de8ea32b45",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2025-02-05T19:34:23Z",
"title_canon_sha256": "a77bcbffbf1be4c33bf6845243187031fbe98d36f9a46941a9a7bbb5fc9b99cd"
},
"schema_version": "1.0",
"source": {
"id": "2502.03571",
"kind": "arxiv",
"version": 2
}
}