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The Missing Minimal Pair: Stereotype Evaluation in LLMs

Paper recorded by Signals 4 on 2026-10-06 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-06 on arXiv · recorded by Signals 4 on 2026-10-07

Category: cs.CL · 自然语言处理 · first seen 2026-10-07

Abstract

A common approach to measuring bias in Large Language Models is to compare the log-likelihoods of two contrastive stereotype sentences. We argue that such single-pair comparisons are often unreliable: simply rewriting the same stereotype with an alternative attribute can yield logically inconsistent preferences. To address this, we propose a dual minimal pair setup that introduces two axes of comp

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#307 most recent of 660 cs.CL papers we have recorded · ↑ newer: GAGR-Lab: Evaluating Joint Spatial-Geometric and Analytic Function Rea · ↓ older: A Systematic Study of Semantic ID Spaces for Generative Information Re
Cite this page: The Missing Minimal Pair: Stereotype Evaluation in LLMs: the #307 most recent of 660 cs.CL papers we have recorded (as of 2026-10-06). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/the-missing-minimal-pair-stereotype-evaluation-in-llms.html
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