Copies or Sources? Measuring How LLM Aggregators Count Restated Evidence in Multi-Agent Systems

Excerpt

arXiv:2610.06192v1 Announce Type: new Abstract: Multi-agent systems built on large language models (LLMs) restate observations as a matter of course: relays forward them, shared boards repeat them and discussion rounds echo them. An aggregator that pools such messages should count sources, not statements. We convert a reported probability into units of independent readings, which assigns every restatement a copy weight, 0 for an aggregator that counts sources and 1 for one that counts every stat