Pith Number
pith:VCIF3LNY
pith:2018:VCIF3LNYHFZLHE2H2H7JBUNZRJ
not attested
not anchored
not stored
refs pending
Gradient Layer: Enhancing the Convergence of Adversarial Training for Generative Models
arxiv:1801.02227 v2 · 2018-01-07 · stat.ML · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{VCIF3LNYHFZLHE2H2H7JBUNZRJ}
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
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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 | 2026-05-18T00:13:19.429128Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
a8905dadb83972b39347d1fe90d1b98a77537f95152d6c587011b3d146759e92
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/VCIF3LNYHFZLHE2H2H7JBUNZRJ \
| 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: a8905dadb83972b39347d1fe90d1b98a77537f95152d6c587011b3d146759e92
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "5de43020d115414d1ef1dada0c1bd466808bfd7e6d88469e4b677fe0f5c70a31",
"cross_cats_sorted": [
"cs.LG"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "stat.ML",
"submitted_at": "2018-01-07T18:44:10Z",
"title_canon_sha256": "fa277eba6f2b08f8439432ca1313238559f6f4e0480badcaba3ef2de8513b28a"
},
"schema_version": "1.0",
"source": {
"id": "1801.02227",
"kind": "arxiv",
"version": 2
}
}