Not All Flips Are Conformity: Decomposing Stance Convergence in Multi-Agent LLM Debate

• URL: http://arxiv.org/abs/2606.00820v1
• Date: Sat, 30 May 2026 17:41:11 GMT
• Title: Not All Flips Are Conformity: Decomposing Stance Convergence in Multi-Agent LLM Debate
• Abstract summary: We show that a conventional answer flip rate conflates three mechanisms: spontaneous instability, stance-induced conformity, and reasoning-induced persuasion.<n>Our three-source decomposition framework isolates each through controlled counterfactual conditions.
• Score: 5.650336594658653
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Multi-agent debate (MAD) is a promising strategy for improving LLM reasoning, but when agents converge on a shared answer, it is unclear whether that convergence reflects genuine deliberation or social compliance. We show that the conventional answer flip rate conflates three distinct mechanisms: spontaneous instability, stance-induced conformity, and reasoning-induced persuasion. Our three-source decomposition framework isolates each through controlled counterfactual conditions. In the primary MMLU-Pro setting, 37% of agent-question observations change under self-reflection alone, while robustness tests show substantial model-dependent instability across GPQA-Diamond and three model families; strict conformity is 29% in the primary setting and remains predominantly harmful across model replications (57-77% correct-to-wrong). A controlled information-gradient experiment reveals that even vacuous reasoning is associated with 20-39% error adoption among resistant agents, with reasoning-like presentation carrying substantial persuasive weight. Harmful conformity can be predicted from Round 0 features (AUC = 0.79), and risk-targeted intervention reduces it by 13.6 percentage points (p < 0.001). However, without correctness labels or self-reflection controls, reducing peer adoption does not improve accuracy, because harmful and beneficial influence cannot be distinguished.

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