4 papers
Directional Hallucinations: Ideological Drift in News-Grounded LLM Question Answering
Chendi Wang, Liam Cunningham, Tom Yishay +1
Large language models (LLMs) are increasingly used to answer questions about political information, including in election-adjacent information settings where factual errors and ide…
Uncovering Political Bias in Large Language Models using Parliamentary Voting Records
Jieying Chen, Karen de Jong, Andreas Poole +4
As large language models (LLMs) become deeply embedded in digital platforms and decision-making systems, concerns about their political biases have grown. While substantial work ha…
Discrimination by LLMs: Cross-lingual Bias Assessment and Mitigation in Decision-Making and Summarisation
Willem Huijzer, Jieying Chen
The rapid integration of Large Language Models (LLMs) into various domains raises concerns about societal inequalities and information bias. This study examines biases in LLMs rela…
Detecting Linguistic Bias in Government Documents Using Large language Models
Milena de Swart, Floris den Hengst, Jieying Chen
This paper addresses the critical need for detecting bias in government documents, an underexplored area with significant implications for governance. Existing methodologies often…