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DyMT-ESB: Dynamic Multi-Turn Evaluation of Social Bias in User-LLM Interactions

arXiv · AI, language, vision and robotics · article · Sep 16, 2026 · UTC

Warning: This paper contains examples of stereotypes and social bias. LLMs are increasingly used in interactive settings by the general public, making the evaluation of model behavior in multi-turn conversational scenarios important for safety, including stereotyping-related harms. However, existing multi-turn social bias evaluations often rely on pre-specified or template-based user inputs that do not adapt to model responses and typically assume a fixed dialogue length in advance. In this paper, we study social bias dynamics in response-conditioned multi-turn interactions using a controlled

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