Pith Number
pith:ZUEB7VGE
pith:2024:ZUEB7VGEQ4WCOIPWFLM2UMJIG7
not attested
not anchored
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refs pending
Large Language Models for Constructing and Optimizing Machine Learning Workflows: A Survey
arxiv:2411.10478 v2 · 2024-11-11 · cs.LG · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{ZUEB7VGEQ4WCOIPWFLM2UMJIG7}
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
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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 | 2026-07-05T09:54:05.790914Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
cd081fd4c4872c2721f62ad9aa312837eacb09e97b1d86c0dcf6e6f1ab37f6e5
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/ZUEB7VGEQ4WCOIPWFLM2UMJIG7 \
| 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: cd081fd4c4872c2721f62ad9aa312837eacb09e97b1d86c0dcf6e6f1ab37f6e5
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "53525f62a1272d5cae7cbcc7a78861ef2066a76329a7a7cd3a4d35925e5a6a91",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2024-11-11T21:54:26Z",
"title_canon_sha256": "4b7388f4ae5a05cbdd14c5d7489436000754d21fb9d22cd74abad736ae97381f"
},
"schema_version": "1.0",
"source": {
"id": "2411.10478",
"kind": "arxiv",
"version": 2
}
}