Pith Number
pith:C5DINAXF
pith:2019:C5DINAXFSNMZK6FXSJFZBQNNHX
not attested
not anchored
not stored
refs pending
Equalizing Gender Biases in Neural Machine Translation with Word Embeddings Techniques
arxiv:1901.03116 v2 · 2019-01-10 · cs.CL
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{C5DINAXFSNMZK6FXSJFZBQNNHX}
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.
Receipt and verification
| First computed | 2026-05-17T23:44:29.611632Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
17468682e593599578b7924b90c1ad3dec882307a617aad094c1119ea5140c62
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/C5DINAXFSNMZK6FXSJFZBQNNHX \
| 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: 17468682e593599578b7924b90c1ad3dec882307a617aad094c1119ea5140c62
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "98113575c4ad5ec02b82fcb4d24fc4fe851031ef3ec3ef2f68980df437cf8ad9",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by-nc-sa/4.0/",
"primary_cat": "cs.CL",
"submitted_at": "2019-01-10T12:06:31Z",
"title_canon_sha256": "f34e3808dc5c4c0cc4faff19c0ded4420beedfe3f9da93c5702378a5b69c5a55"
},
"schema_version": "1.0",
"source": {
"id": "1901.03116",
"kind": "arxiv",
"version": 2
}
}