mlsanityData to 7 Oct 2026

More Debate, Same Evidence: Structural Limits of Homogeneous Multi-Agent Groundedness

arXiv 2608.00243 ↗First posted 31 Jul 2026cs.AIcited by 0

On the map: LLM agents and tool use → Social simulation and multi-agent debate

Abstract (arXiv)

Large language model (LLM) judges are increasingly organized as multi-agent panels under the assumption that exchanging critiques improves judgment quality. We test this assumption for groundedness verification, where a judge must determine whether a claim is supported by the supplied evidence. We evaluate a homogeneous three-agent panel on six public fact-verification and hallucination-detection benchmarks. Relative to a fixed single-agent reference, the panel's system-level accuracy difference ranges from +8.5 to -4.4 percentage points: two datasets show reliable gains, one shows a reliable loss, and three are statistically inconclusive. Because the reference and panel use different model variants, these differences characterize the complete systems rather than isolate a causal debate effect.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Social simulation and multi-agent debate, one of 16 directions in LLM agents and tool use. Builds on 12 of its 22 references that are in the map. First posted on arXiv 31 Jul 2026.

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12 of 22 references.

References · 12

  1. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,393
  2. 2023G-Eval: NLG Evaluation using GPT-4 with Better Human Alignmentcited by 2,205
  3. 2023Improving Factuality and Reasoning in Language Models through Multiagent Debatecited by 1,739
  4. 2020Fact or Fiction: Verifying Scientific Claimscited by 546
  5. 2025GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learningcited by 449
  6. 2023RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Modelscited by 272
  7. 2021Get Your Vitamin C! Robust Fact Verification with Contrastive Evidencecited by 222
  8. 2022ROSCOE: A Suite of Metrics for Scoring Step-by-Step Reasoningcited by 175
  9. 2023WiCE: Real-World Entailment for Claims in Wikipediacited by 118
  10. 2024MMREC: LLM Based Multi-Modal Recommender Systemcited by 22
  11. 2025DLRREC: Denoising Latent Representations via Multi-Modal Knowledge Fusion in Deep Recommender Systemscited by 5
  12. 2026Deep Neural Network Architectures for Electrocardiogram Classification: A Comprehensive Evaluationcited by 2

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  1. 2026The Confident Liar: Diagnosing Multi-Agent Debate with Log-Probabilities and LLM-as-Judge
  2. 2026The Reasoning Trap: An Information-Theoretic Bound on Closed-System Multi-Step LLM Reasoning
  3. 2024Towards Detecting LLMs Hallucination via Markov Chain-based Multi-agent Debate Framework
  4. 2026When Is a Multi-Agent Code Judge Actually Grounded? Two Label-Free Measurements, and a Judge That Declines to Guess
  5. 2026Group Perspective Matters: Regulating Debate Relationships Can Mitigate Blind Conformity in Multi-Agent Debate
  6. 2026Beyond Symmetric Agents: Cognitive Diversity and Multi-Agent Debate in Small Language Models
  7. 2025Judging with Many Minds: Do More Perspectives Mean Less Prejudice? On Bias Amplifications and Resistance in Multi-Agent Based LLM-as-Judge
  8. 2026GSAR: Typed Grounding for Hallucination Detection and Recovery in Multi-Agent LLMs