Pith Number
pith:3IFEMZQS
pith:2023:3IFEMZQS26DYROR5D43CBQJMDY
not attested
not anchored
not stored
refs pending
How Does In-Context Learning Help Prompt Tuning?
arxiv:2302.11521 v1 · 2023-02-22 · cs.CL
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{3IFEMZQS26DYROR5D43CBQJMDY}
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
✓
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 | 2026-07-05T05:44:44.443690Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
da0a466612d78788ba3d1f3620c12c1e30ab119b6103ca1292989b88923b4587
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/3IFEMZQS26DYROR5D43CBQJMDY \
| 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: da0a466612d78788ba3d1f3620c12c1e30ab119b6103ca1292989b88923b4587
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "f2ebdeb70d45b0f16fda6d7d89af8cb4414d7e6efcde993b0474de44aa45661e",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.CL",
"submitted_at": "2023-02-22T17:45:12Z",
"title_canon_sha256": "3ea3f23e1573ad74b65994bcf71a016e6caae4920a49de64a5407e0b1d392367"
},
"schema_version": "1.0",
"source": {
"id": "2302.11521",
"kind": "arxiv",
"version": 1
}
}