Pith Number
pith:AG7Z7QMT
pith:2024:AG7Z7QMTCNZUTRPCWPAANNDIYF
not attested
not anchored
not stored
refs pending
ADO-LLM: Analog Design Bayesian Optimization with In-Context Learning of Large Language Models
arxiv:2406.18770 v2 · 2024-06-26 · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{AG7Z7QMTCNZUTRPCWPAANNDIYF}
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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
SABLE: An NDA-Safe Closed-Loop LLM Framework for Analog Circuit Optimization in Industrial EDA Flows
Receipt and verification
| First computed | 2026-07-05T10:43:36.563859Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
01bf9fc193137349c5e2b3c006b468c17e06a18c935d1ea1673302257025c506
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/AG7Z7QMTCNZUTRPCWPAANNDIYF \
| 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: 01bf9fc193137349c5e2b3c006b468c17e06a18c935d1ea1673302257025c506
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "c7fda1d2f2473eb20e7e179a4620d2e300d97ed2c603244493eb96bbeb576730",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by-nc-sa/4.0/",
"primary_cat": "cs.LG",
"submitted_at": "2024-06-26T21:42:50Z",
"title_canon_sha256": "69e43c7a5d4d51185992b3a4e5b9c8709e48f358279c8d44bb1870e752a8f6b8"
},
"schema_version": "1.0",
"source": {
"id": "2406.18770",
"kind": "arxiv",
"version": 2
}
}