Pith Number
pith:S2SJHQMJ
pith:2024:S2SJHQMJQ6IMH7KZCM34MWWURD
not attested
not anchored
not stored
refs pending
Auto-Regressive Moving Diffusion Models for Time Series Forecasting
arxiv:2412.09328 v1 · 2024-12-12 · cs.LG · cs.AI · stat.AP
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{S2SJHQMJQ6IMH7KZCM34MWWURD}
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 | 2026-07-05T09:48:23.261082Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
96a493c1898790c3fd591337c65ad488d8fb17b41fac4dc4b0d6eaa194d7bb45
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/S2SJHQMJQ6IMH7KZCM34MWWURD \
| 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: 96a493c1898790c3fd591337c65ad488d8fb17b41fac4dc4b0d6eaa194d7bb45
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "db65173d0358445d7a2dd92177201ff06b08a05a52bddd5eb6a89d6e5bf5ceee",
"cross_cats_sorted": [
"cs.AI",
"stat.AP"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2024-12-12T14:51:48Z",
"title_canon_sha256": "732ff083e85ce405972c653f941017e32df845097475a5a5389d9fed7a5a9261"
},
"schema_version": "1.0",
"source": {
"id": "2412.09328",
"kind": "arxiv",
"version": 1
}
}