Pith Number
pith:25JTGUI5
pith:2022:25JTGUI57B74NEEI25RPVADBWO
not attested
not anchored
not stored
refs pending
Can deep neural networks learn process model structure? An assessment framework and analysis
arxiv:2202.11985 v1 · 2022-02-24 · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{25JTGUI57B74NEEI25RPVADBWO}
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
✓
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 | 2026-07-05T04:09:01.883977Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
d75333511df87fc69088d762fa8061b395b13c61adc62a24ed07bb2c36a68334
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/25JTGUI57B74NEEI25RPVADBWO \
| 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: d75333511df87fc69088d762fa8061b395b13c61adc62a24ed07bb2c36a68334
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "46a4335a05c53314bd7919381787e108428fc3dea32ad37675324940a2519f1c",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.LG",
"submitted_at": "2022-02-24T09:44:13Z",
"title_canon_sha256": "9028e800ad759e3ed98b7b5caf708cba59acecd624cd9f6ab92dc114f4423e5b"
},
"schema_version": "1.0",
"source": {
"id": "2202.11985",
"kind": "arxiv",
"version": 1
}
}