Pith Number
pith:IGX4FC6H
pith:2025:IGX4FC6H23Y2IEYILS5FNYHB26
not attested
not anchored
not stored
refs pending
Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models
arxiv:2505.13973 v1 · 2025-05-20 · cs.CL · cs.AI · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{IGX4FC6H23Y2IEYILS5FNYHB26}
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 | 2026-07-05T11:05:54.122906Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
41afc28bc7d6f1a413085cba56e0e1d7b5e341b11f1b63ac4868250af7512cfd
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/IGX4FC6H23Y2IEYILS5FNYHB26 \
| 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: 41afc28bc7d6f1a413085cba56e0e1d7b5e341b11f1b63ac4868250af7512cfd
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "78b1be3e543d18419a12858b2350e594511648372184bbf66a744f384cc52857",
"cross_cats_sorted": [
"cs.AI",
"cs.CV"
],
"license": "http://creativecommons.org/licenses/by-nc-sa/4.0/",
"primary_cat": "cs.CL",
"submitted_at": "2025-05-20T06:12:20Z",
"title_canon_sha256": "2e2d1390f023370033d07fd8f5cc6fbc757955ebe6adae1a7e11e22ab11e5699"
},
"schema_version": "1.0",
"source": {
"id": "2505.13973",
"kind": "arxiv",
"version": 1
}
}