Pith Number
pith:YXUVRP56
pith:2016:YXUVRP56GGIOSYOZAMYHY4LYHQ
not attested
not anchored
not stored
refs pending
Socratic Learning: Augmenting Generative Models to Incorporate Latent Subsets in Training Data
arxiv:1610.08123 v4 · 2016-10-25 · cs.LG · stat.ML
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{YXUVRP56GGIOSYOZAMYHY4LYHQ}
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.
Cited by
Receipt and verification
| First computed | 2026-05-18T00:34:10.251193Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
c5e958bfbe3190e961d903307c71783c1b809cef5f0ebe3ba556c813bb9b091b
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/YXUVRP56GGIOSYOZAMYHY4LYHQ \
| 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: c5e958bfbe3190e961d903307c71783c1b809cef5f0ebe3ba556c813bb9b091b
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "d1516d986f77bb774752c4dd46f7793a938f40022567fe5847bbc53d7c634c08",
"cross_cats_sorted": [
"stat.ML"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2016-10-25T23:43:49Z",
"title_canon_sha256": "42a9fdcc2da5fe02efb19662b7ba04ee57b6c72d9dcf80994d973b856802454a"
},
"schema_version": "1.0",
"source": {
"id": "1610.08123",
"kind": "arxiv",
"version": 4
}
}