Pith Number
pith:5QMXNH4Y
pith:2022:5QMXNH4YQLY2HSZRF2UJYL54HW
not attested
not anchored
not stored
refs pending
When Should We Prefer Offline Reinforcement Learning Over Behavioral Cloning?
arxiv:2204.05618 v1 · 2022-04-12 · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{5QMXNH4YQLY2HSZRF2UJYL54HW}
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 | 2026-07-05T04:14:00.275128Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
ec19769f9882f1a3cb312ea89c2fbc3d93d0265d73dc2f5c0adc2a84a09cbf14
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/5QMXNH4YQLY2HSZRF2UJYL54HW \
| 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: ec19769f9882f1a3cb312ea89c2fbc3d93d0265d73dc2f5c0adc2a84a09cbf14
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "426daff6eb055232ea91e9fba08134e66531421c51bf7fcfa901a7feed22b4d5",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.LG",
"submitted_at": "2022-04-12T08:25:34Z",
"title_canon_sha256": "30f81c6da18a28d098f0e68b2de10d1ac7302c98e73da5a4df08c4503f1466dd"
},
"schema_version": "1.0",
"source": {
"id": "2204.05618",
"kind": "arxiv",
"version": 1
}
}