11 citations · 25 across the 7 of their papers we have counts for
8 papers
What can Neural Referential Form Selectors Learn?
Guanyi Chen, Fahime Same, Kees van Deemter
Despite achieving encouraging results, neural Referring Expression Generation models are often thought to lack transparency. We probed neural Referential Form Selection (RFS) model…
Lessons from Computational Modelling of Reference Production in Mandarin and English
Guanyi Chen, Kees van Deemter
Referring expression generation (REG) algorithms offer computational models of the production of referring expressions. In earlier work, a corpus of referring expressions (REs) in…
A Text Reassembling Approach to Natural Language Generation
Xiao Li, Kees van Deemter, Chenghua Lin
Recent years have seen a number of proposals for performing Natural Language Generation (NLG) based in large part on statistical techniques. Despite having many attractive features…
What do you mean, BERT? Assessing BERT as a Distributional Semantics Model
Timothee Mickus, Denis Paperno, Mathieu Constant +1
Contextualized word embeddings, i.e. vector representations for words in context, are naturally seen as an extension of previous noncontextual distributional semantic models. In th…
Meteorologists and Students: A resource for language grounding of geographical descriptors
Alejandro Ramos-Soto, Ehud Reiter, Kees van Deemter +2
We present a data resource which can be useful for research purposes on language grounding tasks in the context of geographical referring expression generation. The resource is com…
An Empirical Approach for Modeling Fuzzy Geographical Descriptors
Alejandro Ramos-Soto, Jose M. Alonso, Ehud Reiter +2
We present a novel heuristic approach that defines fuzzy geographical descriptors using data gathered from a survey with human subjects. The participants were asked to provide grap…