Big Generalizations with Small Data: Exploring the Role of Training Samples in Learning Adjectives of Size

no code implementations • WS 2019 • S Pezzelle, ro, Raquel Fern{\'a}ndez

In this paper, we experiment with a recently proposed visual reasoning task dealing with quantities {--} modeling the multimodal, contextually-dependent meaning of size adjectives ({`}big{'}, {`}small{'}) {--} and explore the impact of varying the training data on the learning behavior of a state-of-art system.

Small Data Image Classification Visual Reasoning

Is the Red Square Big? MALeViC: Modeling Adjectives Leveraging Visual Contexts

no code implementations • IJCNLP 2019 • S Pezzelle, ro, Raquel Fern{\'a}ndez

This work aims at modeling how the meaning of gradable adjectives of size ({`}big{'}, {`}small{'}) can be learned from visually-grounded contexts.

Quantifiers in a Multimodal World: Hallucinating Vision with Language and Sound

no code implementations • WS 2019 • Alberto Testoni, S Pezzelle, ro, Raffaella Bernardi

Inspired by the literature on multisensory integration, we develop a computational model to ground quantifiers in perception.

Can You See the (Linguistic) Difference? Exploring Mass/Count Distinction in Vision

no code implementations • WS 2017 • David Addison Smith, S Pezzelle, ro, Francesca Franzon, Chiara Zanini, Raffaella Bernardi

Vision and Language Integration: Moving beyond Objects

no code implementations • WS 2017 • Ravi Shekhar, S Pezzelle, ro, Aur{\'e}lie Herbelot, Moin Nabi, Enver Sangineto, Raffaella Bernardi

Action Classification Image Captioning +2

``Look, some Green Circles!'': Learning to Quantify from Images

no code implementations • WS 2016 • Ionut Sorodoc, Angeliki Lazaridou, Gemma Boleda, Aur{\'e}lie Herbelot, S Pezzelle, ro, Raffaella Bernardi

Question Answering Visual Question Answering (VQA)

Building a Bagpipe with a Bag and a Pipe: Exploring Conceptual Combination in Vision

no code implementations • WS 2016 • S Pezzelle, ro, Ravi Shekhar, Raffaella Bernardi