Pith Number
pith:TKMT4HHT
pith:2025:TKMT4HHTTCDOHTPOXLPWXAH4T2
not attested
not anchored
not stored
refs pending
Is Optimal Transport Necessary for Inverse Reinforcement Learning?
arxiv:2506.06793 v1 · 2025-06-07 · cs.LG · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{TKMT4HHTTCDOHTPOXLPWXAH4T2}
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 | 2026-07-05T11:17:55.721876Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
9a993e1cf39886e3cdeebadf6b80fc9ebfcfa91a3168a2b146c2a6801edd138d
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/TKMT4HHTTCDOHTPOXLPWXAH4T2 \
| 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: 9a993e1cf39886e3cdeebadf6b80fc9ebfcfa91a3168a2b146c2a6801edd138d
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "d929b06edc5c44ad3b8fd8a19e42b119489fd7bab083a430ce74cd5c65fae201",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2025-06-07T13:29:37Z",
"title_canon_sha256": "fd8f5a6cce2d813f976d3afd5b91ca470aa05f497d7e30f046c7a0db08c0879a"
},
"schema_version": "1.0",
"source": {
"id": "2506.06793",
"kind": "arxiv",
"version": 1
}
}