Abstract: Traditional user simulators often rely on manually designed agendas, resulting in generated responses lacking diversity and spontaneity. However, building user simulators with large language ...
Abstract: In this paper, we explore the feasibility of leveraging large language models (LLMs) to automate or otherwise assist human raters with identifying harmful content including hate speech, ...
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