Prompted Identity Degrades Cooperation in Multi-Agent LLM Systems
Multi-agent LLM systems increasingly mix models from several providers, yet exposing each agent's underlying model identity to its peers significantly impairs cooperation. We show that when agents are aware of each other's model family, the group splits into clusters, where agents prefer interacting with others carrying their same label, although nothing in the task rewards or asks for such a split. We argue that the label itself causes this split, which we define as $\textit{factionalism}$. We show and measure this phenomenon in two cooperative games and on a reasoning benchmark, with nine to twenty-five agents drawn from up to five open-weight model families. We further show that when t...
| Authors | Xavier Del Giudice, Alessio Palma, Matteo Migliarini et al. |
|---|---|
| Primary category | cs.MA |
| Published | 28 September 2026 |
| Last updated at source | 28 September 2026 |
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