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).

翻译：创世投票将投票解释为关于地面真相的噪音信号。 我们考虑的是真相由一组客观赢家构成的背景, 了解其基本特征的下层和上层界限。 这种背景的一个典型问题是,以事先了解地面真相大小的方式, 将多标签的注解加在一起。 我们制作噪音模型, 我们为这些模型制定规则, 以产生一组最佳赢家。 我们报告多标签注释的实验( 我们收集的 ) 。