Pith Number
pith:XY2FINCJ
pith:2025:XY2FINCJVDBJITVUT24A3UBXFO
not attested
not anchored
not stored
refs pending
ClimateLLM: Efficient Weather Forecasting via Frequency-Aware Large Language Models
arxiv:2502.11059 v1 · 2025-02-16 · cs.LG · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{XY2FINCJVDBJITVUT24A3UBXFO}
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
· sign in to
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 | 2026-07-05T10:15:03.103268Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
be34543449a8c2944eb49eb80dd0372bb318c7cb2a5ae7db1b97da1fd15daecf
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/XY2FINCJVDBJITVUT24A3UBXFO \
| 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: be34543449a8c2944eb49eb80dd0372bb318c7cb2a5ae7db1b97da1fd15daecf
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "5064159e8229e6d43e631ae767a3fa26df82479ebb146beb8325c439b29c3aeb",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.LG",
"submitted_at": "2025-02-16T09:57:50Z",
"title_canon_sha256": "0147218e73d9d5a950d7eba28bec2fc3008e9658bea5f46ef577e3c8c534c462"
},
"schema_version": "1.0",
"source": {
"id": "2502.11059",
"kind": "arxiv",
"version": 1
}
}