Pith Number
pith:NBGFPKUF
pith:2024:NBGFPKUFKVVVHUFWLWNBWW7LXP
not attested
not anchored
not stored
refs pending
MedVisionLlama: Leveraging Pre-Trained Large Language Model Layers to Enhance Medical Image Segmentation
arxiv:2410.02458 v3 · 2024-10-03 · eess.IV · cs.CL · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{NBGFPKUFKVVVHUFWLWNBWW7LXP}
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
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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 | 2026-07-05T11:55:36.406623Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
684c57aa85556b53d0b65d9a1b5bebbbc9f3161ff9c32703ef58d1fdc4ebdcc4
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/NBGFPKUFKVVVHUFWLWNBWW7LXP \
| 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: 684c57aa85556b53d0b65d9a1b5bebbbc9f3161ff9c32703ef58d1fdc4ebdcc4
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "ba5e801a5d3fbfafb4b686ae631316976e03466afcfba9eacfaceb3c20ef1e3a",
"cross_cats_sorted": [
"cs.CL",
"cs.CV"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "eess.IV",
"submitted_at": "2024-10-03T14:50:33Z",
"title_canon_sha256": "1807ff6eaef25b41251654e961e2188954eef51a34f0c9e67b2f418c80e1e6fb"
},
"schema_version": "1.0",
"source": {
"id": "2410.02458",
"kind": "arxiv",
"version": 3
}
}