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pith:BU3UEWO5

pith:2026:BU3UEWO5ENNQLSHBXLMT2OUX4Y
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Training-Free Cultural Alignment of Large Language Models via Persona Disagreement

Chi-Nguyen Tran, Dao Sy Duy Minh, Huynh Trung Kiet, Long Tran-Thanh, Nguyen Lam Phu Quy, Phu-Hoa Pham, The Anh Han, Tuan Nguyen

Disagreement among World Values Survey personas steers black-box LLMs toward country-specific cultural preferences at inference time.

arxiv:2605.10843 v2 · 2026-05-11 · cs.CL · cs.AI · cs.CY

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2 Internet Archive
3 Author claim open · sign in to claim
4 Citations open
5 Replications open
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Claims

C1strongest claim

Across 20 countries and 7 open-weight backbones (2B--70B), DISCA reduces cultural misalignment on MultiTP by 10--24% on the six backbones >=3.8B, and 2--7% on open-ended scenarios, without changing any weights.

C2weakest assumption

That within-country sociodemographic disagreement, when instantiated via World-Values-Survey-grounded persona agents, constitutes the primary and sufficient steering signal for correcting cultural misalignment in black-box LLMs.

C3one line summary

DISCA uses disagreement among WVS-grounded persona panels to apply loss-averse logit corrections that reduce cultural misalignment by 10-24% on MultiTP for models 3.8B and larger, without weight changes.

Formal links

2 machine-checked theorem links

Receipt and verification
First computed 2026-05-20T00:05:46.985676Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

0d374259dd235b05c8e1bad93d3a97e61cbad5293bb2c96740e2c8ef8810673a

Aliases

arxiv: 2605.10843 · arxiv_version: 2605.10843v2 · doi: 10.48550/arxiv.2605.10843 · pith_short_12: BU3UEWO5ENNQ · pith_short_16: BU3UEWO5ENNQLSHB · pith_short_8: BU3UEWO5
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/BU3UEWO5ENNQLSHBXLMT2OUX4Y \
  | 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: 0d374259dd235b05c8e1bad93d3a97e61cbad5293bb2c96740e2c8ef8810673a
Canonical record JSON
{
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    "abstract_canon_sha256": "1187e762c30f58fb65ac401bd1abd805e793a35db9cc374086fa3e407aa93a9c",
    "cross_cats_sorted": [
      "cs.AI",
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    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CL",
    "submitted_at": "2026-05-11T16:55:16Z",
    "title_canon_sha256": "b29eba42aa854c84f53d19899d87438e619c92290f7e49cc2be0695e0fd07885"
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