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pith:MDYTKY3S

pith:2026:MDYTKY3SIV22NHKIUJSOQ7LWJO
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P-Check: Advancing Personalized Reward Model via Learning to Generate Dynamic Checklist

Dongha Lee, Kwangwook Seo

P-Check trains a checklist generator to produce dynamic criteria that align reward models more closely with individual preferences.

arxiv:2601.02986 v3 · 2026-01-06 · cs.CL

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

C1strongest claim

P-Check not only improves reward accuracy but also enhances downstream personalized generation, and remains robust in OOD scenarios.

C2weakest assumption

That a learned checklist generator can reliably synthesize dynamic, multi-faceted criteria that capture nuanced personal judgment without introducing artifacts or requiring user-specific data beyond what static baselines already use.

C3one line summary

P-Check advances personalized reward modeling by training a dynamic checklist generator and preference-contrastive weighting to improve reward accuracy, downstream generation, and OOD robustness.

Formal links

2 machine-checked theorem links

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1 paper in Pith

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First computed 2026-06-23T03:13:53.111918Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

60f13563724575a69d48a264e87d764b9af931c7642c290d48a671d43568b4a4

Aliases

arxiv: 2601.02986 · arxiv_version: 2601.02986v3 · doi: 10.48550/arxiv.2601.02986 · pith_short_12: MDYTKY3SIV22 · pith_short_16: MDYTKY3SIV22NHKI · pith_short_8: MDYTKY3S
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/MDYTKY3SIV22NHKIUJSOQ7LWJO \
  | 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: 60f13563724575a69d48a264e87d764b9af931c7642c290d48a671d43568b4a4
Canonical record JSON
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    "license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
    "primary_cat": "cs.CL",
    "submitted_at": "2026-01-06T12:53:53Z",
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