Pith Number
pith:V7IJ2BNY
pith:2022:V7IJ2BNYAW5YIOAVBVTIR2CP2Z
not attested
not anchored
not stored
refs pending
How does the pre-training objective affect what large language models learn about linguistic properties?
arxiv:2203.10415 v1 · 2022-03-20 · cs.CL
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{V7IJ2BNYAW5YIOAVBVTIR2CP2Z}
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
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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.
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Receipt and verification
| First computed | 2026-07-05T04:06:52.699489Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
afd09d05b805bb8438150d6688e84fd6751fb9b841d3f25305adff9b1a8f979e
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/V7IJ2BNYAW5YIOAVBVTIR2CP2Z \
| 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: afd09d05b805bb8438150d6688e84fd6751fb9b841d3f25305adff9b1a8f979e
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "7154f9ff5077e50b09ae22de844a6d85fef6980437f00a75ea127aea22df6b0e",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.CL",
"submitted_at": "2022-03-20T00:02:10Z",
"title_canon_sha256": "c00ccb3469078e532622eed6cc4ce607fe74f4e8268304b79df11be2a9bf294f"
},
"schema_version": "1.0",
"source": {
"id": "2203.10415",
"kind": "arxiv",
"version": 1
}
}