Pith Number
pith:KZP6QXMO
pith:2025:KZP6QXMOL6BP5NMJT6KJGZ2OMP
not attested
not anchored
not stored
refs pending
ProxSparse: Regularized Learning of Semi-Structured Sparsity Masks for Pretrained LLMs
arxiv:2502.00258 v2 · 2025-02-01 · cs.LG · cs.CL
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{KZP6QXMOL6BP5NMJT6KJGZ2OMP}
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 | 2026-07-05T11:26:02.805968Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
565fe85d8e5f82feb5899f9493674e63e25dae51365f8c43763050fb2dec95f3
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/KZP6QXMOL6BP5NMJT6KJGZ2OMP \
| 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: 565fe85d8e5f82feb5899f9493674e63e25dae51365f8c43763050fb2dec95f3
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "0ad83a71241f4a60f5f4fada7d04d4894bc82b191ce62c18aace05da9c10df15",
"cross_cats_sorted": [
"cs.CL"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.LG",
"submitted_at": "2025-02-01T01:35:23Z",
"title_canon_sha256": "78699494ba9bafeab07c8acdb2b9a6c52a91ecf4595f90fa7cc1b39063721ba6"
},
"schema_version": "1.0",
"source": {
"id": "2502.00258",
"kind": "arxiv",
"version": 2
}
}