Pith Number

pith:RMCEY4XH

pith:2026:RMCEY4XHGKMWGO6ZUBPR27A2Y6

not attested not anchored not stored refs pending

Score-Repellent Monte Carlo: Toward Efficient Non-Markovian Sampler with Constant Memory in General State Spaces

Bohyung Han, Do Young Eun, Geeho Kim, Jie Hu, Jinyoung Choi, Lingyun Chen

Score-Repellent Monte Carlo reduces asymptotic sampling variance as O(1/α) using constant-memory history summaries in general state spaces.

arxiv:2604.22948 v2 · 2026-04-24 · cs.LG · stat.CO · stat.ML

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\usepackage{pith}
\pithnumber{RMCEY4XHGKMWGO6ZUBPR27A2Y6}

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3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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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.

Claims

C1strongest claim

We further identify regimes in which the asymptotic covariance decreases as α increases, with scaling O(1/α), extending the near-zero-variance effect of finite-state history-dependent samplers to general state spaces with constant memory.

C2weakest assumption

The assumptions required for the stochastic approximation analysis with controlled Markovian noise hold for the chosen base kernel and target distribution, allowing the coupled history recursion and estimators to converge as claimed.

C3one line summary

SRMC creates a history-dependent surrogate target via exponential tilt of a running score average, enabling non-Markovian sampling with O(1/alpha) asymptotic variance reduction and constant memory in general state spaces.

Receipt and verification

First computed	2026-05-26T01:02:34.303572Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

8b044c72e73299633bd9a05f1d7c1ac7ae1836724b3c63448ff454cfd2a4c6d0

Aliases

arxiv: 2604.22948 · arxiv_version: 2604.22948v2 · doi: 10.48550/arxiv.2604.22948 · pith_short_12: RMCEY4XHGKMW · pith_short_16: RMCEY4XHGKMWGO6Z · pith_short_8: RMCEY4XH

Agent API

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/RMCEY4XHGKMWGO6ZUBPR27A2Y6 \
  | 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: 8b044c72e73299633bd9a05f1d7c1ac7ae1836724b3c63448ff454cfd2a4c6d0

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "9475268832afb4bfef63d9a21a88ab10e5a9eb968dbbe3e336da951dbed1e746",
    "cross_cats_sorted": [
      "stat.CO",
      "stat.ML"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-04-24T18:39:50Z",
    "title_canon_sha256": "1012eb50c61139aad8b6ad90aa31e15ee17077552c33ae668784296c5cd41b7a"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.22948",
    "kind": "arxiv",
    "version": 2
  }
}