Consensus and Factual Dynamics in Large Populations of Interacting Language Models
3.40T1 sourcearXiv cs.MA
Source record
Published by arXiv cs.MA (T1 source). The original is at https://arxiv.org/abs/2609.39211.
Pipeline notes
The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.
SummaryIntroduces RHEON, a physics-inspired framework modeling populations of frozen LLM agents as a spin system across interaction topologies and temperatures. Sweeps 432 configurations to release the Eraclitus-4.7M corpus. Finds that consensus gain peaks early, more neighbors speed convergence, hallucination-minimising temperature depends on coupling topology, and unanimity does not certify factual correctness.
Why it mattersConcrete empirical warnings for multi-agent builders: topology and temperature coupling matter, and agreement is not a truth signal. The released 4.7M corpus is reusable for further study.
Cited by
No citations on record.