Papers by Charlott Jakob

2 papers
Fine-tuning with Hierarchical Prompting for Robust Propaganda Classification Across Annotation Schemas (2026.findings-acl)

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Challenge: Propaganda detection in social media is challenging due to noisy, short texts and low annotation agreements.
Approach: They propose a new intent-focused taxonomy of propaganda techniques and compare it against an established, higher-agreement schema.
Outcome: The proposed taxonomy outperforms existing models and reveals methodological differences hidden in base models.
PolBiX: Detecting LLMs’ Political Bias in Fact-Checking through X-phemisms (2025.findings-emnlp)

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Challenge: a few models show tendencies of political bias, but this is not mitigated by explicitly calling for objectivism in prompts.
Approach: They investigate political bias by exchanging words with euphemisms or dysphemismas in German claims.
Outcome: The proposed model shows that political bias influences truthfulness assessment more than political leaning .

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