Pith Number
pith:ALZWIJTE
pith:2023:ALZWIJTE3K2TMYZK46XPIBZ2KL
not attested
not anchored
not stored
refs pending
Why Is Prompt Tuning for Vision-Language Models Robust to Noisy Labels?
arxiv:2307.11978 v1 · 2023-07-22 · cs.CV · cs.AI · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{ALZWIJTE3K2TMYZK46XPIBZ2KL}
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
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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 | 2026-07-05T06:33:37.020996Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
02f3642664dab536632ae7aef4073a52f7ae4f513b8ff27624322c904f6e558f
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/ALZWIJTE3K2TMYZK46XPIBZ2KL \
| 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: 02f3642664dab536632ae7aef4073a52f7ae4f513b8ff27624322c904f6e558f
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "d8bfe1c2815b80c8e8c69b23cdb63c2a718dfc91ff4d111e304e85315be220b4",
"cross_cats_sorted": [
"cs.AI",
"cs.LG"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2023-07-22T04:20:30Z",
"title_canon_sha256": "40002de67eab914aea6c8f0c6c2aae808d71c4ae9928349ddbabf60d87fbd370"
},
"schema_version": "1.0",
"source": {
"id": "2307.11978",
"kind": "arxiv",
"version": 1
}
}