Pith Number

pith:BYY5H3QV

pith:2020:BYY5H3QV75D2Y32IH3UN33WLGM

not attested not anchored not stored refs pending

Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning

Ming Yin, Yu Bai, Yu-Xiang Wang

arxiv:2007.03760 v2 · 2020-07-07 · cs.LG · cs.AI · stat.ML

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{BYY5H3QV75D2Y32IH3UN33WLGM}

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Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ 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

1 paper in Pith

Stationary Robust Mean-Field Games under Model Mismatches

Receipt and verification

First computed	2026-07-05T01:55:29.262863Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

0e31d3ee15ff47ac6f483ee8ddeecb331feeec59faed62e9e592a127c4d0f670

Aliases

arxiv: 2007.03760 · arxiv_version: 2007.03760v2 · doi: 10.48550/arxiv.2007.03760 · pith_short_12: BYY5H3QV75D2 · pith_short_16: BYY5H3QV75D2Y32I · pith_short_8: BYY5H3QV

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/BYY5H3QV75D2Y32IH3UN33WLGM \
  | 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: 0e31d3ee15ff47ac6f483ee8ddeecb331feeec59faed62e9e592a127c4d0f670

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "1afcfa8f42e83f442c3e4ae13474eae6f738165f19b5ce61e97e4d4991bd7cf3",
    "cross_cats_sorted": [
      "cs.AI",
      "stat.ML"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2020-07-07T19:44:14Z",
    "title_canon_sha256": "6a10551798d13e78194118dff984040f7fd1c54eb0978e0ac29e4f6383c70816"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2007.03760",
    "kind": "arxiv",
    "version": 2
  }
}