Loop-Back Authority in LLM Agent Teams: A Paired Experiment on Flat and Hierarchical Coordination

arXiv:2609.14767 · cs.MA, cs.AI, cs.CL, econ.GN, q-fin.EC · Submitted 2026-09-13 · Read on arXiv

cs.MA, cs.AI, cs.CL, econ.GN, q-fin.EC

Submitted: 2026-09-13

Updated: 2026-10-07

Comments: 8 pages, 3 figures, 3 tables, plus 21 pages of supplementary material. Code: https://github.com/cihatburak/Master_Thesis_Multi_Agents

Code: https://github.com/cihatburak/Master_Thesis_Multi_Agents

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Accuracy — 31× in this paper · explained in 1 episode
• Lexical Diversity — 12× in this paper · explained in 2 episodes
• Robustness — 10× in this paper · explained in 5 episodes
• alpha — 10× in this paper · explained in 1 episode
• Actionability — 8× in this paper · explained in 3 episodes
• Sycophancy — 8× in this paper · explained in 4 episodes
• Core — 7× in this paper · explained in 2 episodes
• Multi-Agent System — 7× in this paper · explained in 6 episodes
• Trace — 7× in this paper · explained in 2 episodes
• Calibration — 5× in this paper · explained in 7 episodes
• LLM judge — 5× in this paper · explained in 2 episodes
• Leiden Institute of Advanced Computer Science — 5× in this paper
• Benchmark — 4× in this paper · explained in 2 episodes
• Embeddings — 4× in this paper · explained in 2 episodes
• Generative AI — 4× in this paper · explained in 2 episodes
• LLM-as-a-Judge — 4× in this paper · explained in 3 episodes
• Commentary — 3× in this paper · explained in 2 episodes
• Verifier — 3× in this paper · explained in 2 episodes
• AI Agents — 2× in this paper · explained in 2 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Alignment — 2× in this paper · explained in 1 episode
• Hallucination — 2× in this paper · explained in 3 episodes
• Multi-Agent Framework — 2× in this paper · explained in 3 episodes
• Multi-agent Collaboration — 2× in this paper · explained in 2 episodes
• Multi-agent Collaborative Framework — 2× in this paper · explained in 2 episodes
• Verification — 2× in this paper · explained in 2 episodes
• Abstention — 1× in this paper · explained in 1 episode
• Agent Architectures — 1× in this paper · explained in 1 episode
• Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Data Provenance — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Provenance — 1× in this paper · explained in 4 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes

Sources

• AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation
• ReAct: Synergizing Reasoning and Acting in Language Models
• G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment
• Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena
• Adaptive Semi-Supervised Segmentation of Brain Vessels with Ambiguous Labels
• Constitutional AI: Harmlessness from AI Feedback
• Multi-Agent Collaboration Mechanisms: A Survey of LLMs
• Topological Structure Learning Should Be A Research Priority for LLM-Based Multi-Agent Systems
• Towards Understanding Sycophancy in Language Models
• Why Do Multi-Agent LLM Systems Fail?
• Can Lessons From Human Teams Be Applied to Multi-Agent Systems? The Role of Structure, Diversity, and Interaction Dynamics
• Reliable agent engineering should integrate machine-compatible organizational principles
• OrgAgent: Organize Your Multi-Agent System like a Company
• Recipes for Creativity: Iterative Generation and Evaluation in Large Language Models
• Measuring Concept Content in Text from LLM Activations: ESG Evidence from Concept Vectors and Linear Probes

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