Abstract. Recent research has enabled important progress in developing agents aimed at real-world linguistic interaction with humans. Hence, within the general shift of research focus from "information" to "knowledge", an important question is how to apply large-scale knowledge resources in order to improve agents' capabilities of linguistic interaction with humans. This paper presents research toward an efficient representation of the necessary perceptual knowledge in dialogue with a particular focus on reference expressions. We generalize an existing formal model of reference expressions involving perceptual grouping in order to account for a number of types of reference expressions that the previous model could not account for. Our model yields an increase in both coverage and accuracy of referent identification - which has been confirmed in preliminary experiments. We outline an algorithm for the future application of this model to other languages, showing ...