Pith Number
pith:A6GNWMHY
pith:2025:A6GNWMHYN3PLCUQM62HH5EYQEC
not attested
not anchored
not stored
refs pending
TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning
arxiv:2504.18348 v1 · 2025-04-25 · cs.CV · cs.AI · cs.CR
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{A6GNWMHYN3PLCUQM62HH5EYQEC}
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.
Receipt and verification
| First computed | 2026-07-05T10:54:05.812462Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
078cdb30f86edeb1520cf68e7e931020afeaf1dd9f3ec8d9607649c5ae3e2ffd
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/A6GNWMHYN3PLCUQM62HH5EYQEC \
| 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: 078cdb30f86edeb1520cf68e7e931020afeaf1dd9f3ec8d9607649c5ae3e2ffd
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "b79de03319c2ddfcf34869b698ab60d532ad399b2e5d101c9165c7cbd95a9910",
"cross_cats_sorted": [
"cs.AI",
"cs.CR"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2025-04-25T13:36:50Z",
"title_canon_sha256": "8a77286ae8e6443a43063aaf8c1c183fa1e06ac9ed852eb55b473cd03aaf0e11"
},
"schema_version": "1.0",
"source": {
"id": "2504.18348",
"kind": "arxiv",
"version": 1
}
}