Pith Number
pith:NJPUXRYR
pith:2024:NJPUXRYRF65RGE236L6G7YLY2G
not attested
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refs pending
Crafting Efficient Fine-Tuning Strategies for Large Language Models
arxiv:2407.13906 v1 · 2024-07-18 · cs.CL · cs.AI · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{NJPUXRYRF65RGE236L6G7YLY2G}
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Record completeness
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4
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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
Fine-tuning vs. In-context Learning in Large Language Models: A Formal Language Learning Perspective
Fine-tuning vs. In-context Learning in Large Language Models: A Formal Language Learning Perspective
Receipt and verification
| First computed | 2026-07-05T08:45:55.312841Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
6a5f4bc7112fbb13135bf2fc6fe178d1bf9590398d188a6fc6485743dfbfe540
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/NJPUXRYRF65RGE236L6G7YLY2G \
| 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: 6a5f4bc7112fbb13135bf2fc6fe178d1bf9590398d188a6fc6485743dfbfe540
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "b2b091433ca5315bdf940b7c025d8d988301582400259a0d93748f6367547baa",
"cross_cats_sorted": [
"cs.AI",
"cs.LG"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.CL",
"submitted_at": "2024-07-18T21:36:00Z",
"title_canon_sha256": "902076e8b79ba57fd8457588baa84cd3bd64699d47b883426e9d426057b2bbb1"
},
"schema_version": "1.0",
"source": {
"id": "2407.13906",
"kind": "arxiv",
"version": 1
}
}