[2603.23406] Beyond Preset Identities: How Agents Form Stances and Boundaries in Generative Societies

Computer Science > Artificial Intelligence arXiv:2603.23406 (cs) [Submitted on 24 Mar 2026] Title:Beyond Preset Identities: How Agents Form Stances and Boundaries in Generative Societies Authors:Hanzhong Zhang, Siyang Song, Jindong Wang View a PDF of the paper titled Beyond Preset Identities: How Agents Form Stances and Boundaries in Generative Societies, by Hanzhong Zhang and 2 other authors View PDF HTML (experimental) Abstract:While large language models simulate social behaviors, their capacity for stable stance formation and identity negotiation during complex interventions remains unclear. To overcome the limitations of static evaluations, this paper proposes a novel mixed-methods framework combining computational virtual ethnography with quantitative socio-cognitive profiling. By embedding human researchers into generative multiagent communities, controlled discursive interventions are conducted to trace the evolution of collective cognition. To rigorously measure how agents internalize and react to these specific interventions, this paper formalizes three new metrics: Innate Value Bias (IVB), Persuasion Sensitivity, and Trust-Action Decoupling (TAD). Across multiple representative models, agents exhibit endogenous stances that override preset identities, consistently demonstrating an innate progressive bias (IVB > 0). When aligned with these stances, rational persuasion successfully shifts 90% of neutral agents while maintaining high trust. In contrast, conflicting...