Pith Number
pith:COX6IANJ
pith:2024:COX6IANJB37CRB6MWLUPJ5LMM4
not attested
not anchored
not stored
refs pending
DiffStitch: Boosting Offline Reinforcement Learning with Diffusion-based Trajectory Stitching
arxiv:2402.02439 v2 · 2024-02-04 · cs.LG · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{COX6IANJB37CRB6MWLUPJ5LMM4}
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
· sign in to
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 | 2026-07-05T07:48:03.402434Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
13afe401a90efe2887ccb2e8f4f56c6716d9568a8ee601d7b1f6f0603b93d3d8
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/COX6IANJB37CRB6MWLUPJ5LMM4 \
| 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: 13afe401a90efe2887ccb2e8f4f56c6716d9568a8ee601d7b1f6f0603b93d3d8
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "50f6f365881b00f44eebadab372e44b8975270e1e9a76267fa98be274f95c773",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2024-02-04T10:30:23Z",
"title_canon_sha256": "4f67be5be57f93f258002d8ebf00be131e98225a570a6fea24ae2e5764a309f3"
},
"schema_version": "1.0",
"source": {
"id": "2402.02439",
"kind": "arxiv",
"version": 2
}
}