Pith Number
pith:VNZCR7JU
pith:2024:VNZCR7JUXJJFV4OYE4SIR5XGPK
not attested
not anchored
not stored
refs pending
Deep Learning Inference on Heterogeneous Mobile Processors: Potentials and Pitfalls
arxiv:2405.01851 v1 · 2024-05-03 · cs.LG · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{VNZCR7JUXJJFV4OYE4SIR5XGPK}
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 | 2026-07-05T08:15:02.982794Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
ab7228fd34ba525af1d8272488f6e67ab0d2737c5ab9c5eda3a883cf8a9b33b8
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/VNZCR7JUXJJFV4OYE4SIR5XGPK \
| 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: ab7228fd34ba525af1d8272488f6e67ab0d2737c5ab9c5eda3a883cf8a9b33b8
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "f9894ad1e3c3a6ee02e80f2f9570b2e151af65792177704aeb3a25ef8d89607c",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2024-05-03T04:47:23Z",
"title_canon_sha256": "9b78eb12805d8b309b25120bcb0d5264240decb11afc042736a7121886bea394"
},
"schema_version": "1.0",
"source": {
"id": "2405.01851",
"kind": "arxiv",
"version": 1
}
}