AIBearisharXiv – CS AI · 7h ago7/10
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Argument Collapse: LLMs Flatten Long-Form Public Debate
A new study reveals that large language models generate significantly less diverse arguments than humans when responding to public debates, with only 3.4% of LLM main arguments being unique compared to 65.3% for human responses. This 'argument collapse' phenomenon persists even when models are prompted to generate diverse answers, suggesting LLMs may homogenize public discourse by repeatedly introducing the same polished arguments across different contexts.