Pith Number
pith:SYL5T4FT
pith:2024:SYL5T4FTQUDOHSFBMT7ROV5NHQ
not attested
not anchored
not stored
refs pending
FSTA-SNN:Frequency-based Spatial-Temporal Attention Module for Spiking Neural Networks
arxiv:2501.14744 v2 · 2024-12-15 · cs.NE · cs.CV · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{SYL5T4FTQUDOHSFBMT7ROV5NHQ}
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 | 2026-07-05T10:09:52.045899Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
9617d9f0b38506e3c8a164ff1757ad3c27f69b5667ad84a1d35433e7434b47e3
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/SYL5T4FTQUDOHSFBMT7ROV5NHQ \
| 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: 9617d9f0b38506e3c8a164ff1757ad3c27f69b5667ad84a1d35433e7434b47e3
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "39db49d799fdb86be89ab896afd1db3a93cfd46b7e38bcce47164edbe73b0e15",
"cross_cats_sorted": [
"cs.CV",
"cs.LG"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.NE",
"submitted_at": "2024-12-15T08:23:58Z",
"title_canon_sha256": "8af3694b54b37534042b307c273c02118a12b262f38e463cf83a0e656e945c5a"
},
"schema_version": "1.0",
"source": {
"id": "2501.14744",
"kind": "arxiv",
"version": 2
}
}