Expressed personality in LLM dialogues is shaped by trait prompts, roles, and styles in trait-specific ways, with similar patterns in English and Japanese.
ArXiv:2302.03848 [cs]
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High agreeableness in LLM voice assistants increases older adults' empathy perceptions and real-time explanations outperform history-based ones, but personality does not affect perceived intelligence.
Medium personality expression in LLM agents yields the most positive user perceptions in goal-oriented tasks, further improved by trait alignment.
Sketches a conceptual framework for adapting conversational agents' personas and personality expression levels to task context, user goals, and urgency.
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