most citedWhat Vision-Language Models `See' when they See Scenes

8 citations · 11 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CL2022

Understanding Cross-modal Interactions in V&L Models that Generate Scene Descriptions

Michele Cafagna, Kees van Deemter, Albert Gatt

Image captioning models tend to describe images in an object-centric way, emphasising visible objects. But image descriptions can also abstract away from objects and describe the t…

cs.CL2022

Assessing Neural Referential Form Selectors on a Realistic Multilingual Dataset

Guanyi Chen, Fahime Same, Kees van Deemter

Previous work on Neural Referring Expression Generation (REG) all uses WebNLG, an English dataset that has been shown to reflect a very limited range of referring expression (RE) u…

cs.CL20221 cited

Understanding the Use of Quantifiers in Mandarin

Guanyi Chen, Kees van Deemter

We introduce a corpus of short texts in Mandarin, in which quantified expressions figure prominently. We illustrate the significance of the corpus by examining the hypothesis (know…

cs.CL2022

The Role of Explanatory Value in Natural Language Processing

Kees van Deemter

A key aim of science is explanation, yet the idea of explaining language phenomena has taken a backseat in mainstream Natural Language Processing (NLP) and many other areas of Arti…

cs.CL20222 cited

Semeval-2022 Task 1: CODWOE -- Comparing Dictionaries and Word Embeddings

Timothee Mickus, Kees van Deemter, Mathieu Constant +1

Word embeddings have advanced the state of the art in NLP across numerous tasks. Understanding the contents of dense neural representations is of utmost interest to the computation…

cs.LO2022

Evaluating Automatic Difficulty Estimation of Logic Formalization Exercises

Alexandra Mayn, Kees van Deemter

Teaching logic effectively requires an understanding of the factors which cause logic students to struggle. Formalization exercises, which require the student to produce a formula…