Pith Number
pith:IKXJME4E
pith:2024:IKXJME4EPI4HRUO65G6XKE5Z5K
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not stored
refs pending
Tuning Large Multimodal Models for Videos using Reinforcement Learning from AI Feedback
arxiv:2402.03746 v3 · 2024-02-06 · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{IKXJME4EPI4HRUO65G6XKE5Z5K}
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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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 | 2026-07-05T08:32:36.028833Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
42ae9613847a3878d1dee9bd7513b9eabefad1f2e40f3ce53c449529c49d854b
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/IKXJME4EPI4HRUO65G6XKE5Z5K \
| 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: 42ae9613847a3878d1dee9bd7513b9eabefad1f2e40f3ce53c449529c49d854b
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "f4be818d69ff4a2872023bffbb1f74b64675b4f04c8dc895abff27834e65b768",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by-nc-sa/4.0/",
"primary_cat": "cs.CV",
"submitted_at": "2024-02-06T06:27:40Z",
"title_canon_sha256": "4cd032d67fabe68512c3bc661cb48a1e793174300d49c696731ca33c1607f086"
},
"schema_version": "1.0",
"source": {
"id": "2402.03746",
"kind": "arxiv",
"version": 3
}
}