Pith Number
pith:7TAD7M7O
pith:2024:7TAD7M7OKC6MJG3KAFMNICPVWP
not attested
not anchored
not stored
refs pending
Angry Men, Sad Women: Large Language Models Reflect Gendered Stereotypes in Emotion Attribution
arxiv:2403.03121 v3 · 2024-03-05 · cs.CL
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{7TAD7M7OKC6MJG3KAFMNICPVWP}
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
· sign in to
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 | 2026-07-05T08:24:03.461659Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
fcc03fb3ee50bcc49b6a0158d409f5b3de6c073e95695e88c4b24ac0fe6995f6
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/7TAD7M7OKC6MJG3KAFMNICPVWP \
| 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: fcc03fb3ee50bcc49b6a0158d409f5b3de6c073e95695e88c4b24ac0fe6995f6
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "4370d18ca548032c978b6847a0393f1427a66bcec5af627aa0ae89b90f26b0fe",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.CL",
"submitted_at": "2024-03-05T17:04:05Z",
"title_canon_sha256": "b0b4a5e8a091cc231ad3003ff6d3990f51c48f237e6bcdc43889bac0e9eefd39"
},
"schema_version": "1.0",
"source": {
"id": "2403.03121",
"kind": "arxiv",
"version": 3
}
}