Truth or Tribe: How In-group Favoritism Prioritize Facts in Persona Agents
arXiv cs.AI / 5/5/2026
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Key Points
- The paper investigates whether in-group favoritism—previously observed in social behavior and also in generative language models—shows up in persona agents when they encounter contradicting information such as misinformation.
- Using a proposed “Truth or Tribe” simulation framework with triadic interactions, the authors find persona agents strongly prefer identity-similar peers, accepting incorrect answers at much higher rates than from dissimilar peers.
- The study shows in-group favoritism persists even in defeasible reasoning settings where there is no absolute truth, and it becomes more pronounced as cognitive complexity increases.
- To reduce these bias effects, the authors propose three intervention strategies: Identity-Blind Instruction, Structured Counterfactual Reasoning, and a Heterogeneous Perspective Ensemble.
- Overall, the results highlight a specific failure mode for persona-agent cooperation under conflicting information and provide concrete mitigation approaches for future research and system design.
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