Pith Number
pith:SG3W3IG7
pith:2021:SG3W3IG7EQYVO2GJNRXYAD6I2M
not attested
not anchored
not stored
refs pending
What Changes Can Large-scale Language Models Bring? Intensive Study on HyperCLOVA: Billions-scale Korean Generative Pretrained Transformers
arxiv:2109.04650 v2 · 2021-09-10 · cs.CL
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{SG3W3IG7EQYVO2GJNRXYAD6I2M}
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
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4
Citations
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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 | 2026-07-05T03:35:32.551673Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
91b76da0df24315768c96c6f800fc8d31552558fe63573deb3af9f62a55a25e6
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/SG3W3IG7EQYVO2GJNRXYAD6I2M \
| 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: 91b76da0df24315768c96c6f800fc8d31552558fe63573deb3af9f62a55a25e6
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "431ae8c8e1a1714782165837f71237e18bcd5cfa100fcfb6434f894d436fb179",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.CL",
"submitted_at": "2021-09-10T03:32:19Z",
"title_canon_sha256": "64d19524ae4f31e40172b45c9727cf3f6470cb8f69d950a789ed981b133cef89"
},
"schema_version": "1.0",
"source": {
"id": "2109.04650",
"kind": "arxiv",
"version": 2
}
}