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Sebastian Padó

ACL 2026×2对齐与偏好社会与人本可解释性
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0 一作 · 2 篇 · ACL 2026

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2026 顶会论文

2
作者位次 #4/4ACL 2026Poster· Natural Language Processing

One Persona, Many Cues, Different Results: How Sociodemographic Cues Impact LLM Personalization

Franziska Weeber · Vera Neplenbroek · Jan Batzner · Sebastian Padó

摘要

Personalization of LLMs by sociodemographic subgroup often improves user experience, but can also introduce or amplify biases and unfair outcomes across groups. Prior work has employed so-called personas, sociodemographic user attributes conveyed to a model, to study bias in LLMs by relying on a...

对齐与偏好社会与人本OpenReview 项目页
作者位次 #3/4ACL 2026Findings· Findings of ACL

Beyond Marginal Distributions: A Framework to Evaluate the Representativeness of Demographic-Aligned LLM s

Tristan Williams · Franziska Weeber · Sebastian Padó · Alan Akbik

摘要

Large language models are increasingly used to represent human opinions, values, or beliefs, and their steerability towards these ideals is an active area of research. Existing work focuses predominantly on aligning marginal response distributions, treating each alignment evaluation example indep...

社会与人本对齐与偏好可解释性OpenReview 项目页

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