Measuring Collapse and Correction in Homogeneous-Panel LLM Debate

arXiv:2609.35279 · cs.CL · Submitted 2026-09-28 · Read on arXiv

cs.CL

Submitted: 2026-09-28

Updated: 2026-09-28

Project page: https://lixin.ai/DebateLedger

Terminology

• Accuracy — 90× in this paper · explained in 1 episode
• Trace — 83× in this paper · explained in 2 episodes
• alpha — 26× in this paper · explained in 1 episode
• AUC — 24× in this paper · explained in 2 episodes
• Benchmark — 19× in this paper · explained in 2 episodes
• Aggregation — 15× in this paper · explained in 1 episode
• Robustness — 11× in this paper · explained in 5 episodes
• Provenance — 10× in this paper · explained in 3 episodes
• Sycophancy — 10× in this paper · explained in 4 episodes
• Consistency — 7× in this paper · explained in 3 episodes
• Ablation — 5× in this paper · explained in 1 episode
• Calibration — 5× in this paper · explained in 7 episodes
• Abstention — 3× in this paper · explained in 1 episode
• Self-consistency — 3× in this paper · explained in 2 episodes
• Dynamic Round Selection — 2× in this paper
• Failure Modes — 2× in this paper · explained in 3 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• LLM judge — 2× in this paper · explained in 2 episodes
• Large Language Model (LLM) — 2× in this paper · explained in 3 episodes
• Multi-Agent System — 2× in this paper · explained in 6 episodes
• Selection Bias — 2× in this paper · explained in 4 episodes
• Area Under the Curve (AUC) — 1× in this paper · explained in 1 episode
• Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
• Deferral — 1× in this paper · explained in 2 episodes
• Exchangeability — 1× in this paper · explained in 2 episodes
• Homogeneity — 1× in this paper · explained in 2 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Residualization — 1× in this paper · explained in 2 episodes
• Scaling Laws — 1× in this paper · explained in 4 episodes

Sources

• CGES: Confidence-Guided Early Stopping for Efficient and Accurate Self-Consistency
• Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
• Debate Only When Necessary: Adaptive Multiagent Collaboration for Efficient LLM Reasoning
• Too Polite to Disagree: Understanding Sycophancy Propagation in Multi-Agent Systems
• LLMs Know They're Wrong and Agree Anyway: The Shared Sycophancy-Lying Circuit
• The Sequential Edge: Inverse-Entropy Voting Beats Parallel Self-Consistency at Matched Compute
• The Value of Variance: Mitigating Debate Collapse in Multi-Agent Systems via Uncertainty-Driven Policy Optimization
• Simple synthetic data reduces sycophancy in large language models
• Can LLM Agents Really Debate? A Controlled Study of Multi-Agent Debate in Logical Reasoning
• Talk Isn't Always Cheap: Understanding Failure Modes in Multi-Agent Debate
• Knowledge Divergence and the Value of Debate for Scalable Oversight
• Disentangling the Drivers of LLM Social Conformity: An Uncertainty-Moderated Dual-Process Mechanism
• Demystifying Multi-Agent Debate: The Role of Confidence and Diversity

Related papers

• Exploring Solution Divergence and Its Effect on Large Language Model Problem Solving
• Ishigaki-IDS-Bench: A Benchmark for Generating Information Delivery Specification from BIM Information Requirements
• Subliminal Steering: Stronger Encoding of Hidden Signals
• MedStruct-S: A Benchmark for Key Discovery, Key-Conditioned QA and Semi-Structured Extraction from OCR Clinical Reports
• The End of Transformers? On Challenging Attention and the Rise of Sub-Quadratic Architectures
• Untangling the Mechanisms of Misleading Context in Medical Question Answering