Lost in Communication: Uncertainty Propagation in Multi-Agent Systems

In multi-agent systems of large language models, the agent that observes uncertain evidence is often not the one that acts on it, so the uncertainty must propagate through hand-offs. We propose a controlled experimental design for uncertainty propagation, implemented in UPMAS. Only the irreducible uncertainty of the evidence varies, and systematic differences in behavior are causally attributable to this uncertainty. Across three open-weight models, uncertainty metrics barely react to the induced uncertainty, even at the agent that observes the evidence, and what little they register fades within a few steps. In their messages, agents omit the information three times as often after the first hand-off as before (37% against 11%) and otherwise mostly assert one possible state of the world as certain. We call this loss of uncertainty between the evidence and the actions that depend on it vanishing uncertainty. The acting agent’s own uncertainty quantification cannot recover uncertainty lost upstream, so multi-agent systems must propagate uncertainty through their messages.