Who cites «Measuring Political Bias in Large Language Models: What Is Said and How It Is Said»
- IssueBench: Millions of Realistic Prompts for Measuring Issue Bias in LLM Writing AssistanceTransactions of the Association for Computational Linguistics (TACL)Paul Röttger, Musashi Hinck, Valentin Hofmann, et al.2026 · 16 citations
- LLMs Struggle to Reject False Presuppositions when Misinformation Stakes are HigharXiv:2505.22354Judith Sieker, Clara Lachenmaier, Sina Zarrieß2025 · 10 citations
- Framing Political Bias in Multilingual LLMs Across Pakistani LanguagesAnnual Meeting of the Association for Computational Linguistics (ACL)Afrozah Nadeem, Mark Dras, Usman Naseem2026 · 4 citations
- Democratic or Authoritarian? Probing a New Dimension of Political Biases in Large Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)David Guzman Piedrahita, Irene Strauss, Rada Mihalcea, et al.2026 · 3 citations
- PsychEthicsBench: Evaluating Large Language Models Against Australian Mental Health EthicsFindings of the Association for Computational LinguisticsYaling Shen, Stephanie Fong, Yiwen Jiang, et al.2026 · 2 citations
- When Do Language Models Endorse Limitations on Human Rights Principles?Findings of the Association for Computational LinguisticsKeenan Samway, Miu Nicole Takagi, Rada Mihalcea, et al.2026 · 1 citation
- Can Persona-Prompted LLMs Emulate Subgroup Values? An Empirical Analysis of Generalisability and Fairness in Cultural AlignmentAnnual Meeting of the Association for Computational Linguistics (ACL)Bryan Chen Zhengyu Tan, Zhengyuan Liu, Xiaoyuan Yi, et al.2026
- News Credibility Assessment by LLMs and Humans: Implications for Political BiasWorkshop on Computational Approaches to Subjectivity, Sentiment and Social Media AnalysisPia Wenzel Neves, Charlott Jakob, Vera Schmitt2026
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