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Memory Correlation Bias can mislead multi-agent systems into false majorities, but CAMA effectively counters this by recovering independent evidence from correlated memories.
LLM agents can be made more reliable by structurally verifying their internal reasoning, rather than relying on consensus which conflates agreement with faithfulness.
