  Epistemic voting interprets votes as noisy signals about a ground truth. We
consider contexts where the truth consists of a set of objective winners,
knowing a lower and upper bound on its cardinality. A prototypical problem for
this setting is the aggre-gation of multi-label annotations with prior
knowledge on the size of the ground truth. We posit noisemodels, for which we
define rules that output an optimal set of winners. We report on experiments on
multi-label annotations (which we collected).
