Pith Number
pith:RXCW2X7Z
pith:2018:RXCW2X7ZVPMJVZOGO7GAW24LWF
not attested
not anchored
not stored
refs pending
One-Shot High-Fidelity Imitation: Training Large-Scale Deep Nets with RL
arxiv:1810.05017 v1 · 2018-10-11 · cs.LG · cs.AI · cs.CV · cs.RO
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{RXCW2X7ZVPMJVZOGO7GAW24LWF}
Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more
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 | 2026-05-18T00:03:35.213127Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
8dc56d5ff9abd89ae5c677cc0b6b8bb17c05d048635a8a55ac324143340e6992
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/RXCW2X7ZVPMJVZOGO7GAW24LWF \
| 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: 8dc56d5ff9abd89ae5c677cc0b6b8bb17c05d048635a8a55ac324143340e6992
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "c44ab855f8367176e62d249d39e01353921166424c18f486ccb5a8cfdf1ae9df",
"cross_cats_sorted": [
"cs.AI",
"cs.CV",
"cs.RO"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2018-10-11T13:46:18Z",
"title_canon_sha256": "628ccceb3a2e49774dc63ab3c322616cb51488427573672ef45cc890586e2bb3"
},
"schema_version": "1.0",
"source": {
"id": "1810.05017",
"kind": "arxiv",
"version": 1
}
}