Pith Number
pith:7T3US32J
pith:2024:7T3US32JDLOZJHDNSBLZI77A5Y
not attested
not anchored
not stored
refs pending
MING-MOE: Enhancing Medical Multi-Task Learning in Large Language Models with Sparse Mixture of Low-Rank Adapter Experts
arxiv:2404.09027 v1 · 2024-04-13 · cs.CL
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{7T3US32JDLOZJHDNSBLZI77A5Y}
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 | 2026-07-05T08:07:44.000757Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
fcf7496f491add949c6d9057947fe0ee0347cb46dcdb2bf89750215e0cf47391
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/7T3US32JDLOZJHDNSBLZI77A5Y \
| 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: fcf7496f491add949c6d9057947fe0ee0347cb46dcdb2bf89750215e0cf47391
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "8ac4f0a80e847681a2a384951d5a44c4e290d197a76463f48b9b116354feee24",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CL",
"submitted_at": "2024-04-13T15:28:52Z",
"title_canon_sha256": "f9704342db37f1ea18d8b46fdb06b3772e159e90f9d0d78edbfd68a2e29031fc"
},
"schema_version": "1.0",
"source": {
"id": "2404.09027",
"kind": "arxiv",
"version": 1
}
}