Pith Number
pith:JRO3VGWH
pith:2024:JRO3VGWHMZNSYMPA7D4MLWFIJO
not attested
not anchored
not stored
refs pending
Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators
arxiv:2401.17548 v6 · 2024-01-31 · cs.LG · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{JRO3VGWHMZNSYMPA7D4MLWFIJO}
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.
Cited by
Receipt and verification
| First computed | 2026-07-05T08:54:46.770914Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
4c5dba9ac7665b2c31e0f8f8c5d8a84ba5e5d3adf72b58a5336468f8463f5fba
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/JRO3VGWHMZNSYMPA7D4MLWFIJO \
| 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: 4c5dba9ac7665b2c31e0f8f8c5d8a84ba5e5d3adf72b58a5336468f8463f5fba
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "f630aa962f644cc16e9908f4455f4d84292567ae9db3c52b93810721c77276d3",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2024-01-31T02:26:09Z",
"title_canon_sha256": "347f514d745370c104c6d01e68e3a043cb2c48b6e189fe211a7d5f7fc5ad0586"
},
"schema_version": "1.0",
"source": {
"id": "2401.17548",
"kind": "arxiv",
"version": 6
}
}