In recent years, several machine learning models have been proposed. They are trained
with a language modelling objective on large-scale text-only data. With such pretraining …

Humans have remarkable capacity to reason abductively and hypothesize about what lies
beyond the literal content of an image. By identifying concrete visual clues scattered …

Intelligent systems that aim at mastering language as humans do must deal with its semantic
underspecification, namely, the possibility for a linguistic signal to convey only part of the …

Answering a question that is grounded in an image is a crucial ability that requires
understanding the question, the visual context, and their interaction at many linguistic levels …

With a fast developing pace of geographic applications, automatable and intelligent models
are essential to be designed to handle the large volume of information. However, few …

Causal reasoning is fundamental to human intelligence and crucial for effective decision-
making in real-world environments. Despite recent advancements in large vision-language …

We aim to automatically identify human action reasons in online videos. We focus on the
widespread genre of lifestyle vlogs, in which people perform actions while verbally …

Images can be described in terms of the objects they contain, or in terms of the types of
scene or place that they instantiate. In this paper we address to what extent pretrained …

Current captioning datasets focus on object-centric captions, describing the visible objects in
the image, eg" people eating food in a park". Although these datasets are useful to evaluate …

Thanks to independent advances in language and image generation we could soon be in
the position to have systems that communicate with humans by combining language and …