*=Equal Contributors
Controversy is a mirrored image of our zeitgeist, and an vital facet to any discourse. The rise of enormous language fashions (LLMs) as conversational techniques has elevated public reliance on these techniques for solutions to their numerous questions. Consequently, it’s essential to systematically study how these fashions reply to questions that pertaining to ongoing debates. Nonetheless, few such datasets exist in offering human-annotated labels reflecting the up to date discussions. To foster analysis on this space, we suggest a novel building of a controversial questions dataset, increasing upon the publicly launched Quora Query Pairs Dataset. This dataset presents challenges regarding data recency, security, equity, and bias. We consider totally different LLMs utilizing a subset of this dataset, illuminating how they deal with controversial points and the stances they undertake. This analysis finally contributes to our understanding of LLMs’ interplay with controversial points, paving the best way for enhancements of their comprehension and dealing with of advanced societal debates.