Can structured debate roles help small models detect ambiguity?

Small models (7-9B parameters) individually struggle with ambiguity detection — recognizing when a problem statement is underspecified or admits multiple interpretations. But a structured multi-agent debate protocol with explicit leader-follower roles and rotation significantly boosts performance: Mistral-7B-led debates achieve 76.7% success rate, well beyond single-model baselines.

The protocol matters more than the models. A leader agent proposes an interpretation, two follower agents challenge or extend it, and roles rotate across rounds. The two-follower configuration creates a stronger consensus mechanism than pairwise debate because disagreement must survive two independent challenges rather than one. This is a different mechanism from the general multi-agent debate finding that When does debate actually improve reasoning accuracy? — ambiguity detection is not a verifiability problem but a recognition problem, and the structured role protocol prevents the persuasive-framing failure mode by forcing role rotation.

The result is notable because ambiguity detection is a prerequisite for the information-seeking behavior that models systematically lack. Since Can models identify what information they actually need?, the ability to detect ambiguity is upstream of the ability to ask clarifying questions. Leader-follower debate offers a multi-agent route to a capability that single models achieve at only 40-50% accuracy (QuestBench).

This also connects to the broader finding that Does cognitive diversity alone improve multi-agent ideation quality?. The leader-follower protocol imposes structural diversity through role assignment rather than relying on emergent diversity — a design choice that may explain why it works with small models that individually lack the expertise threshold.

Source: Reasoning Architectures Paper: "Debate for Ambiguity Detection" (2507.12370)