Pith Number
pith:F4DKGRLN
pith:2024:F4DKGRLN5Y6B4ZSMD55YQ44P4U
not attested
not anchored
not stored
refs pending
Breaking the Curse of Dimensionality: Diffusion Models Efficiently Learn Low-Dimensional Distributions
arxiv:2409.02426 v5 · 2024-09-04 · cs.LG · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{F4DKGRLN5Y6B4ZSMD55YQ44P4U}
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
· sign in to
claim
4
Citations
5
Replications
✓
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 | 2026-06-10T01:09:12.893413Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
2f06a3456dee3c1e664c1f7b88738fe5300de641971ad67d64c3048caeaec30b
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/F4DKGRLN5Y6B4ZSMD55YQ44P4U \
| 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: 2f06a3456dee3c1e664c1f7b88738fe5300de641971ad67d64c3048caeaec30b
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "e25f5828cdb21cf4d1d87ccd6a588a83875e7e620b69b09871fe9bac915eb9f9",
"cross_cats_sorted": [
"cs.CV"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.LG",
"submitted_at": "2024-09-04T04:14:02Z",
"title_canon_sha256": "b57a38c5108cf4bc190afcc56da459bbe1b7cf4ecd433273dae39df99d83cb08"
},
"schema_version": "1.0",
"source": {
"id": "2409.02426",
"kind": "arxiv",
"version": 5
}
}