Pith Number
pith:LPSTOVVD
pith:2023:LPSTOVVDPHENHUSHDZDB2KGD7E
not attested
not anchored
not stored
refs pending
MFABA: A More Faithful and Accelerated Boundary-based Attribution Method for Deep Neural Networks
arxiv:2312.13630 v1 · 2023-12-21 · cs.CV · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{LPSTOVVDPHENHUSHDZDB2KGD7E}
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.
Cited by
Receipt and verification
| First computed | 2026-07-05T07:26:47.687587Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
5be53756a379c8d3d2471e461d28c3f92d294da1f761731a52945669583c332d
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/LPSTOVVDPHENHUSHDZDB2KGD7E \
| 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: 5be53756a379c8d3d2471e461d28c3f92d294da1f761731a52945669583c332d
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "797715434c885bb903a830fce8d3c631e9b50166b0fcd2466f3eff7d5cb237f0",
"cross_cats_sorted": [
"cs.LG"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2023-12-21T07:48:15Z",
"title_canon_sha256": "380ecb93578014edcbd6127e2da336882731b90b6a0168c9360b7e40a9f789d0"
},
"schema_version": "1.0",
"source": {
"id": "2312.13630",
"kind": "arxiv",
"version": 1
}
}