Language comprehension requires rapid and flexible access to information stored in long-term memory, likely influenced by activation of rich world knowledge and by brain systems that support the processing of sensorimotor content. We hypothesized that while literal language about biological motion might rely on neurocognitive representations of biological motion specific to the details of the a...

A key task to understand an image and its corresponding caption is not only to find out what is shown on the picture and described in the text, but also what is the exact relationship between these two elements. The long-term objective of our work is to be able to distinguish different types of relationship, including literal vs. non-literal usages, as well as finegrained non-literal usages (i....

There has been an explosion of work in the vision & language community during the past few years from image captioning to video transcription, and answering questions about images. These tasks have focused on literal descriptions of the image. To move beyond the literal, we choose to explore how questions about an image are often directed at commonsense inference and the abstract events evoked ...

We introduce a family of matrices that define logics in which paraconsistency and/or paracompleteness occurs only at the level of literals, that is, formulas that are propositional letters or their iterated negations. We give a sound and complete axiomatization for the logic defined by the class of all these matrices, we give conditions for the maximality of these logics and we study in detail ...

In this paper we introduce the pattern literal reification, a modelling technique to address scenarios, in which we need to bless particular literals, usually when applying data properties, in order to use them as subjects and/or full-fledged objects of semantic assertions.