Multi-agent debate and mixture-of-agents outperform self-consistency by 1.3 and 2.7 percentage points respectively at equal compute budgets on MMLU-Pro and BBH, with advantages that continue at higher scales while self-consistency saturates.
FLOPs are calculated with the formulas from Table 4 of Appendix B
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Multi-Agent Reasoning Improves Compute Efficiency: Pareto-Optimal Test-Time Scaling
Multi-agent debate and mixture-of-agents outperform self-consistency by 1.3 and 2.7 percentage points respectively at equal compute budgets on MMLU-Pro and BBH, with advantages that continue at higher scales while self-consistency saturates.