← Search

Matthias Orlikowski

3 accepted papers

2025

Beyond Demographics: Fine-tuning Large Language Models to Predict Individuals’ Subjective Text Perceptions

ACL 2025long

People naturally vary in their annotations for subjective questions and some of this variation is thought to be due to the person’s sociodemographic characteristics. LLMs have also been used to label data, but recent work has shown that models perform poorly when prompted with sociodemographic attri…

Cited by 0SourcePDFScholar
2023

Architectural Sweet Spots for Modeling Human Label Variation by the Example of Argument Quality: It’s Best to Relate Perspectives!

EMNLP 2023long main

Many annotation tasks in natural language processing are highly subjective in that there can be different valid and justified perspectives on what is a proper label for a given example. This also applies to the judgment of argument quality, where the assignment of a single ground truth is often ques…

Cited by 13SourcecodeScholar
2023

The Ecological Fallacy in Annotation: Modeling Human Label Variation goes beyond Sociodemographics

ACL 2023short

Many NLP tasks exhibit human label variation, where different annotators give different labels to the same texts. This variation is known to depend, at least in part, on the sociodemographics of annotators. Recent research aims to model individual annotator behaviour rather than predicting aggregate…

Cited by 24SourcePDFScholar