Pith Number
pith:BMREARWY
pith:2023:BMREARWYWKYMUI34NTR4PFFYYI
not attested
not anchored
not stored
refs pending
Parallel Trust-Region Approaches in Neural Network Training: Beyond Traditional Methods
arxiv:2312.13677 v1 · 2023-12-21 · math.NA · cs.LG · cs.NA
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{BMREARWYWKYMUI34NTR4PFFYYI}
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.
Receipt and verification
| First computed | 2026-07-05T07:26:48.180228Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
0b224046d8b2b0ca237c6ce3c794b8c20496273536158aec6a0aa7819dfdf5f5
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/BMREARWYWKYMUI34NTR4PFFYYI \
| 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: 0b224046d8b2b0ca237c6ce3c794b8c20496273536158aec6a0aa7819dfdf5f5
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "f20df9a0f63536ae5ef474b404a1b0656af1b3cfcb0b08c3a019abf1c4fc78dd",
"cross_cats_sorted": [
"cs.LG",
"cs.NA"
],
"license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
"primary_cat": "math.NA",
"submitted_at": "2023-12-21T09:00:24Z",
"title_canon_sha256": "0328b0962ec9c28fc15751a59cc6f682551671953de3dac87843586f0a59e872"
},
"schema_version": "1.0",
"source": {
"id": "2312.13677",
"kind": "arxiv",
"version": 1
}
}