Pith Number
pith:5MU7RXHH
pith:2021:5MU7RXHH4C32FAEK6M6EP7ACAK
not attested
not anchored
not stored
refs pending
Multi-Objective Learning to Predict Pareto Fronts Using Hypervolume Maximization
arxiv:2102.04523 v2 · 2021-02-08 · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{5MU7RXHH4C32FAEK6M6EP7ACAK}
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.
Cited by
Receipt and verification
| First computed | 2026-07-05T03:23:38.763280Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
eb29f8dce7e0b7a2808af33c47fc02029a75202989d1f4e17959aff4cf50991b
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/5MU7RXHH4C32FAEK6M6EP7ACAK \
| 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: eb29f8dce7e0b7a2808af33c47fc02029a75202989d1f4e17959aff4cf50991b
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "312c0d5bb25672ddc4c0cb47ad9dd9f24b3c1d40433b4f12d0bafd0c1319032f",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2021-02-08T20:41:21Z",
"title_canon_sha256": "e4e2399a0643c780e8e6b657a81d1de93bd0a12cdd6e83751e8aa665d5769c27"
},
"schema_version": "1.0",
"source": {
"id": "2102.04523",
"kind": "arxiv",
"version": 2
}
}