Pith Number
pith:K3XNYS5F
pith:2024:K3XNYS5F67ENRGOEWTU4XIDL5K
not attested
not anchored
not stored
refs pending
Unleashing The Power of Pre-Trained Language Models for Irregularly Sampled Time Series
arxiv:2408.08328 v2 · 2024-08-12 · cs.AI · cs.LG · stat.AP
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{K3XNYS5F67ENRGOEWTU4XIDL5K}
Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge
Record completeness
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Bitcoin timestamp
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4
Citations
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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 | 2026-07-05T11:16:29.064246Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
56eedc4ba5f7c8d899c4b4e9cba06bea987e3b7d54fd18bab3d8af6a0e1a3d87
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/K3XNYS5F67ENRGOEWTU4XIDL5K \
| 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: 56eedc4ba5f7c8d899c4b4e9cba06bea987e3b7d54fd18bab3d8af6a0e1a3d87
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "ba01b56d6342003f2c1b867e3922da249ba839c19840ef55e6bb702f5ea0d559",
"cross_cats_sorted": [
"cs.LG",
"stat.AP"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.AI",
"submitted_at": "2024-08-12T14:22:14Z",
"title_canon_sha256": "af686207fca77b16467c1f6731ce1fc4ef6676f5e7518572683dc675be500b2b"
},
"schema_version": "1.0",
"source": {
"id": "2408.08328",
"kind": "arxiv",
"version": 2
}
}