Do More Agents Help? Evaluating Accuracy and Cost in LLM Multi-Agent Workflows

arXiv:2606.05670 · cs.AI · Submitted 2026-06-04 · Read on arXiv

cs.AI

Submitted: 2026-06-04

Updated: 2026-10-09

Terminology

• Accuracy — 3× in this paper · explained in 1 episode
• Benchmark — 3× in this paper · explained in 2 episodes
• Protocol-Aligned External — 1× in this paper

Related papers

• MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
• Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
• Agents' Last Exam
• The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
• MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
• Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems