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cs.CL2026
Definitional Sensitivity in Media Bias Detection: A Multi-Definition Dataset and Benchmark
Martin Wessel, Timo Spinde, Jürgen Pfeffer +1
Media bias detection relies on definitions and examples that specify what counts as bias, yet these specifications often vary across datasets or remain implicit, even when given th…
cs.CL2025
Leveraging Large Language Models for Automated Definition Extraction with TaxoMatic A Case Study on Media Bias
Timo Spinde, Luyang Lin, Smi Hinterreiter +1
This paper introduces TaxoMatic, a framework that leverages large language models to automate definition extraction from academic literature. Focusing on the media bias domain, the…
cs.CL2025
The Promises and Pitfalls of LLM Annotations in Dataset Labeling: a Case Study on Media Bias Detection
Tomas Horych, Christoph Mandl, Terry Ruas +4
High annotation costs from hiring or crowdsourcing complicate the creation of large, high-quality datasets needed for training reliable text classifiers. Recent research suggests u…