Deleting the strongest message is not enough: collective dependence analysis cuts controlled multi-agent violations from 93% to 6%
Individually compliant language model agents can still jointly support a policy violation through messages that are harmless one by one. Collective Dependence Analysis (CDA) measures each message's necessity and sufficiency by removing and retaining it, cutting violations from 93% to 6% in controlled conversations and from 98% to 9% in agent-generated operational ones. It returns both an explanation and a minimal intervention set, though jointly required groups resist exact recovery and removals can also disrupt correct decisions.