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Modular Mechanistic Networks for Computational Modelling of Spatial Descriptions

Conference contribution
Authors Simon Dobnik
John D. Kelleher
Published in Abstracts of the Seventh Swedish Language Technology Conference (SLTC-2018), 7-9 November 2018, Stockholm
Place of publication Stockholm, Sweden
Publication year 2018
Published at Department of Philosophy, Linguistics and Theory of Science
Language en
Links sltc2018.su.se/program/
https://gup.ub.gu.se/file/207582
https://gup.ub.gu.se/file/207583
Keywords spatial descriptions deep learning neural networks modular architectures language and vision image captioning
Subject categories Computational linguistics

Abstract

We argue current deep learning approaches to modelling of spatial language in generating image captions have shortcomings and that the multiplicity of factors that influence spatial language invites a modular approach where the solution can be built in a piece-wise manner and then integrated. We call this approach where deep learning is assisted with domain knowledge expressed as modules that are trained on data a top-down or mechanistic approach to otherwise a bottom-up phenomenological approach.

Page Manager: Webmaster|Last update: 9/11/2012
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