Learning Preferences for Referring Expression Generation: Effects of Domain, Language and Algorithm

Trainable Referring Expression Generation using Overspecification Preferences

Referring expression generation (REG) models that use speaker-dependent information require a considerable amount of training data produced by every individual speaker, or may otherwise perform poorly. In this work we pr…

Event versus entity co-reference: Effects of context and form of referring expression

Anaphora resolution systems require both an enumeration of possible candidate antecedents and an identification process of the antecedent. This paper focuses on (i) the impact of the form of referring expression on entit…

Referring Expression Object Segmentation with Caption-Aware Consistency

Referring expressions are natural language descriptions that identify a particular object within a scene and are widely used in our daily conversations. In this work, we focus on segmenting the object in an image specifi…

MuDoCo: Corpus for Multidomain Coreference Resolution and Referring Expression Generation

This paper proposes a new dataset, MuDoCo, composed of authored dialogs between a fictional user and a system who are given tasks to perform within six task domains. These dialogs are given rich linguistic annotations by…

On The Feasibility of Open Domain Referring Expression Generation Using Large Scale Folksonomies