Multi-agent systems homogenize in code generation, hiring, and peer review, and neither sampling stochasticity nor mixed-model configurations mitigates the risk
The study operationalizes homogenization in multi-agent systems through conformity, polarization, and inertia, evaluates it on code generation, hiring, and peer review, and finds that agent interactions reduce diversity and amplify shared failures, while sampling stochasticity and mixed-model configurations fail to mitigate these risks.