Pith Number
pith:CWM5HVYT
pith:2025:CWM5HVYT3WSXJ7HN5YGZ5B3P5P
not attested
not anchored
not stored
refs pending
Enhancing Reinforcement Learning in 3D Environments through Semantic Segmentation: A Case Study in ViZDoom
arxiv:2511.11703 v2 · 2025-11-12 · cs.LG · cs.AI · cs.RO
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{CWM5HVYT3WSXJ7HN5YGZ5B3P5P}
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 | 2026-05-29T01:04:58.146223Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
1599d3d713dda574fcedee0d9e876febf36e17db14f5cbde65dd11bf115aa953
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/CWM5HVYT3WSXJ7HN5YGZ5B3P5P \
| 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: 1599d3d713dda574fcedee0d9e876febf36e17db14f5cbde65dd11bf115aa953
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "c6b1e5006c04c1c12f9d0afed221318c6bc2fc211222776fa034bc3b30922254",
"cross_cats_sorted": [
"cs.AI",
"cs.RO"
],
"license": "http://creativecommons.org/licenses/by-sa/4.0/",
"primary_cat": "cs.LG",
"submitted_at": "2025-11-12T14:28:46Z",
"title_canon_sha256": "6ce620efbb1cec256afedf74de242c57f24dc0b1b6135a2c01b43bf6dedb7e24"
},
"schema_version": "1.0",
"source": {
"id": "2511.11703",
"kind": "arxiv",
"version": 2
}
}