Pith Number
pith:FSJV5RRQ
pith:2016:FSJV5RRQMZPHUXOXOESOEOOCQ5
not attested
not anchored
not stored
refs pending
Effective Quantization Methods for Recurrent Neural Networks
arxiv:1611.10176 v1 · 2016-11-30 · cs.LG · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{FSJV5RRQMZPHUXOXOESOEOOCQ5}
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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 | 2026-05-18T00:56:11.020116Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
2c935ec630665e7a5dd77124e239c28742d133ec4184363ce591ac268131ef43
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/FSJV5RRQMZPHUXOXOESOEOOCQ5 \
| 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: 2c935ec630665e7a5dd77124e239c28742d133ec4184363ce591ac268131ef43
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "91e78391c8ee06f52b5ea9929ced03ef05497bed1fc24553a9245b017fc296c8",
"cross_cats_sorted": [
"cs.CV"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2016-11-30T14:33:08Z",
"title_canon_sha256": "e3bd416d815a037b956deaffebe6de729ddca4da02bc467c7a6c13358e56c9f1"
},
"schema_version": "1.0",
"source": {
"id": "1611.10176",
"kind": "arxiv",
"version": 1
}
}