Using multi-sense embeddings in a hard clustering (rather than single-sense embeddings in a soft clustering) avoids the usage of a cluster membership threshold, which most soft clustering algorithms require.
the clustering algorithm outputs a membership degree for each element and each cluster, i.e., a fuzzy membership.