Introduces Contagion Networks framework and measures preference propagation in 3-agent LLM setups, finding architectural priors dominate prompts, topology affects spread, and larger committees reduce contagion by ~69%.
Towards implicit bias detection and mitigation in multi-agent llm interactions.arXiv preprint arXiv:2410.02584
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Multi-agent systems amplify minor stochastic biases into systemic polarization via echo-chamber effects in structured workflows, even with neutral agents.
A rapid review of fairness in LLM-enabled multi-agent systems for the software development lifecycle concludes that the field lacks standardized evaluations, broad coverage, and effective governance, leaving it unprepared for deployable fair systems.
citing papers explorer
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Contagion Networks: Evaluator Preference Propagation in Multi-Agent LLM Systems
Introduces Contagion Networks framework and measures preference propagation in 3-agent LLM setups, finding architectural priors dominate prompts, topology affects spread, and larger committees reduce contagion by ~69%.
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Aligned Agents, Biased Swarm: Measuring Bias Amplification in Multi-Agent Systems
Multi-agent systems amplify minor stochastic biases into systemic polarization via echo-chamber effects in structured workflows, even with neutral agents.
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Fairness in Multi-Agent Systems for Software Engineering: An SDLC-Oriented Rapid Review
A rapid review of fairness in LLM-enabled multi-agent systems for the software development lifecycle concludes that the field lacks standardized evaluations, broad coverage, and effective governance, leaving it unprepared for deployable fair systems.