Pith Number
pith:7NVZTC7T
pith:2023:7NVZTC7T6QSXJYUIH4RQH2PL3I
not attested
not anchored
not stored
refs pending
Harnessing Mixed Offline Reinforcement Learning Datasets via Trajectory Weighting
arxiv:2306.13085 v1 · 2023-06-22 · cs.LG · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{7NVZTC7T6QSXJYUIH4RQH2PL3I}
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
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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 | 2026-07-05T06:23:51.909043Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
fb6b998bf3f42574e2883f2303e9ebda0ab1c044358ee7afd925071f0c349b62
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/7NVZTC7T6QSXJYUIH4RQH2PL3I \
| 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: fb6b998bf3f42574e2883f2303e9ebda0ab1c044358ee7afd925071f0c349b62
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "002e72918315b985e2928624a80e4a3a1cac3b649ab6fde232da0ca59497bbf0",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.LG",
"submitted_at": "2023-06-22T17:58:02Z",
"title_canon_sha256": "74ce84b4e653c8c59bb6bcc5f5391c17cb0857d23ab1d8eaa38922874f44c7cf"
},
"schema_version": "1.0",
"source": {
"id": "2306.13085",
"kind": "arxiv",
"version": 1
}
}