Pith Number
pith:KHVJTXHU
pith:2019:KHVJTXHUZ7URGEABOLSMGUADCP
not attested
not anchored
not stored
refs pending
Using Approximate Models in Robot Learning
arxiv:1902.04696 v1 · 2019-02-13 · cs.RO
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{KHVJTXHUZ7URGEABOLSMGUADCP}
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.
Receipt and verification
| First computed | 2026-05-17T23:54:06.257473Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
51ea99dcf4cfe913100172e4c3500313d52e5603398ff96320f20266452c0378
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/KHVJTXHUZ7URGEABOLSMGUADCP \
| 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: 51ea99dcf4cfe913100172e4c3500313d52e5603398ff96320f20266452c0378
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "2730be5a3f912bd1482399c3f41d494a0a0416aa03f952e717b05d95c4deded4",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.RO",
"submitted_at": "2019-02-13T01:33:27Z",
"title_canon_sha256": "bcf698a5fa97443093cd75e1ca9047a8f73236b50e7d1b65474dafd2ec6404c1"
},
"schema_version": "1.0",
"source": {
"id": "1902.04696",
"kind": "arxiv",
"version": 1
}
}