Pith Number
pith:7WXFBWRL
pith:2024:7WXFBWRLDWOTJNB4DNI5NMHC2B
not attested
not anchored
not stored
refs pending
Symmetric Reinforcement Learning Loss for Robust Learning on Diverse Tasks and Model Scales
arxiv:2405.17618 v3 · 2024-05-27 · cs.LG · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{7WXFBWRLDWOTJNB4DNI5NMHC2B}
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.
Receipt and verification
| First computed | 2026-07-05T11:25:01.666335Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
fdae50da2b1d9d34b43c1b51d6b0e2d04adf37a804453a535329fd2be8ccff49
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/7WXFBWRLDWOTJNB4DNI5NMHC2B \
| 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: fdae50da2b1d9d34b43c1b51d6b0e2d04adf37a804453a535329fd2be8ccff49
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "c844fd83ab4970458a428c7f7819ac5965411473e5d872de679fd49577de3e41",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2024-05-27T19:28:33Z",
"title_canon_sha256": "610e45d2f405f7af9118997736b70725d7063f04088cda3e1e63b9f811457c2e"
},
"schema_version": "1.0",
"source": {
"id": "2405.17618",
"kind": "arxiv",
"version": 3
}
}