Pith Number
pith:64J6QDUN
pith:2025:64J6QDUNYNOP5773HG4ERPYM3G
not attested
not anchored
not stored
refs pending
Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models
arxiv:2509.03036 v1 · 2025-09-03 · cs.LG · cs.AI · cs.IR · cs.SC
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{64J6QDUNYNOP5773HG4ERPYM3G}
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.
Receipt and verification
| First computed | 2026-07-05T12:04:02.557995Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
f713e80e8dc35cfefffb39b848bf0cd98d73770cd46c8c2bff7d468bdb009d74
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/64J6QDUNYNOP5773HG4ERPYM3G \
| 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: f713e80e8dc35cfefffb39b848bf0cd98d73770cd46c8c2bff7d468bdb009d74
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "31bd04832f246e7ea2427b574f546a84b7a94b92fb021c13385a8503167a82e2",
"cross_cats_sorted": [
"cs.AI",
"cs.IR",
"cs.SC"
],
"license": "http://creativecommons.org/licenses/by-nc-sa/4.0/",
"primary_cat": "cs.LG",
"submitted_at": "2025-09-03T05:53:40Z",
"title_canon_sha256": "5c00a9af88adc9e2915f16def78c7c70b7733c28f262a545ada75d96b223efe6"
},
"schema_version": "1.0",
"source": {
"id": "2509.03036",
"kind": "arxiv",
"version": 1
}
}