Pith Number
pith:FU3UN3TP
pith:2024:FU3UN3TP2ZCGKBEHQTXSDWPCMC
not attested
not anchored
not stored
refs pending
A Method for Evaluating Hyperparameter Sensitivity in Reinforcement Learning
arxiv:2412.07165 v2 · 2024-12-10 · cs.LG · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{FU3UN3TP2ZCGKBEHQTXSDWPCMC}
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
✓
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 | 2026-07-05T10:09:13.276856Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
2d3746ee6fd64465048784ef21d9e260800b1117dae78f468d77f41c7ae4e804
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/FU3UN3TP2ZCGKBEHQTXSDWPCMC \
| 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: 2d3746ee6fd64465048784ef21d9e260800b1117dae78f468d77f41c7ae4e804
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "b8b516cc5fea26cb2837c3abeaa5ba93efa18bf640642c3998e66843bbd8ac16",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.LG",
"submitted_at": "2024-12-10T03:55:18Z",
"title_canon_sha256": "ecf3cc39329e6dacb3a62749f0422d5568b804c52af4dfc8d21a4d53d974b4ce"
},
"schema_version": "1.0",
"source": {
"id": "2412.07165",
"kind": "arxiv",
"version": 2
}
}