Pith Number
pith:HKF57BXG
pith:2024:HKF57BXGM2F2RO7VACXWRCZTOJ
not attested
not anchored
not stored
refs pending
Are LLMs Good Zero-Shot Fallacy Classifiers?
arxiv:2410.15050 v1 · 2024-10-19 · cs.CL
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{HKF57BXGM2F2RO7VACXWRCZTOJ}
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 | 2026-07-05T09:22:49.419252Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
3a8bdf86e6668ba8bbf500af688b33725dcfc3f5d05e05c9d045ab9a804ff79b
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/HKF57BXGM2F2RO7VACXWRCZTOJ \
| 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: 3a8bdf86e6668ba8bbf500af688b33725dcfc3f5d05e05c9d045ab9a804ff79b
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "80516c365aa5a0665d4df629082462ae7478e24cabfe25e872c20297950c0fbd",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CL",
"submitted_at": "2024-10-19T09:38:55Z",
"title_canon_sha256": "086ea3dea9e8afc38ca95db8a3f2e1e411f144d42072482f34e3855bade270f2"
},
"schema_version": "1.0",
"source": {
"id": "2410.15050",
"kind": "arxiv",
"version": 1
}
}