A multi-dimensional audit framework for politically aligned LLMs finds consistent trade-offs: larger models are more effective and truthful but less fair with higher bias, while fine-tuned models reduce bias but increase hallucinations and reasoning decline, and all tested models show deficiencies.
Robust hate speech detection in social media: A cross- dataset empirical evaluation
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A Multi-Dimensional Audit of Politically Aligned Large Language Models
A multi-dimensional audit framework for politically aligned LLMs finds consistent trade-offs: larger models are more effective and truthful but less fair with higher bias, while fine-tuned models reduce bias but increase hallucinations and reasoning decline, and all tested models show deficiencies.