Pith Number
pith:5FWN6UTQ
pith:2022:5FWN6UTQPX53V4MIIGHY7KLHMD
not attested
not anchored
not stored
refs pending
SFMGNet: A Physics-based Neural Network To Predict Pedestrian Trajectories
arxiv:2202.02791 v1 · 2022-02-06 · cs.RO · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{5FWN6UTQPX53V4MIIGHY7KLHMD}
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
✓
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 | 2026-07-05T03:54:33.007882Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
e96cdf52707dfbbaf188418f8fa96760c736a9984e5ae928298273c07fd26d72
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/5FWN6UTQPX53V4MIIGHY7KLHMD \
| 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: e96cdf52707dfbbaf188418f8fa96760c736a9984e5ae928298273c07fd26d72
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "7a66c7df2cbdccd76fb0143f7f28e6fa07e879b22e6bd63b259fe67b080bbc30",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.RO",
"submitted_at": "2022-02-06T14:58:09Z",
"title_canon_sha256": "f677a79c647a2c5f47841d830837316bfe1b87a181d380b33a465eb983c37bf5"
},
"schema_version": "1.0",
"source": {
"id": "2202.02791",
"kind": "arxiv",
"version": 1
}
}