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Why the pond is not outside the frog? Grounding in contextual representations by neural language models


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Title: Why the pond is not outside the frog? Grounding in contextual representations by neural language models
Other Titles: Why the pond is not outside the frog?
Grounding in contextual representations by neural language models
Authors: Ghanimifard, Mehdi
E-mail: mehdi.ghanimifard@gu.se
mehdi.ghanimifard@gmail.com
mmehdi.g@gmail.com
Issue Date: 5-May-2020
University: Göteborgs universitet. Humanistiska fakulteten
University of Gothenburg. Faculty of Arts
Institution: Department of Philosophy, Linguistics and Theory of Science ; Institutionen för filosofi, lingvistik och vetenskapsteori
Parts of work: Dobnik, S., Ghanimifard, M., & Kelleher, J. (2018). Exploring the Functional and Geometric Bias of Spatial Relations Using Neural Language Models. In Proceedings of the First International Workshop on Spatial Language Understanding (pp. 1-11).
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Ghanimifard, M., & Dobnik, S. (2019). What a neural language model tells us about spatial relations. In Proceedings of the Combined Workshop on Spatial Language Understanding (SpLU) and Grounded Communication for Robotics (RoboNLP) (pp. 71-81).
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Dobnik, S., Ghanimifard, M. (2020). Spatial descriptions on a functional-geometric spectrum: the location of objects. Accepted in Spatial Cognition XII, Papers from 12th International Conference, Spatial Cognition 2020/21, Riga, Latvia.

Ghanimifard, M., & Dobnik, S. (2018). Knowing When to Look for What and Where: Evaluating Generation of Spatial Descriptions with Adaptive Attention. In European Conference on Computer Vision (pp. 153-161). Springer, Cham.
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Ghanimifard, M., & Dobnik, S. (2019). What goes into a word: generating image descriptions with top-down spatial knowledge. In Proceedings of the 12th International Conference on Natural Language Generation (pp. 540-551).
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Ghanimifard, M., & Dobnik, S. (2017). Learning to Compose Spatial Relations with Grounded Neural Language Models. In IWCS 2017-12th International Conference on Computational Semantics-Long papers.

Bizzoni, Y., Chatzikyriakidis, S., & Ghanimifard, M. (2017, September). “Deep” Learning: Detecting Metaphoricity in Adjective-Noun Pairs. In Proceedings of the Workshop on Stylistic Variation (pp. 43-52).
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Date of Defence: 2020-05-27
Disputation: 27 maj 2020, kl 15:15, Lilla Hörsalen, C350, Humanisten, Renströmsgatan 6. https://gu-se.zoom.us/j/63108152441?pwd=UDV1NytSM1RuNXE4ZWFieHlyOURxQT09
Degree: Doctor of Philosophy
Publication type: Doctoral thesis
Keywords: Computational linguistics
Language grounding
Spatial language
Distributional semantics
Computer vision
Language modelling
Vision and language
Neural language model
Grounded language model
Abstract: In this thesis, to build a multi-modal system for language generation and understanding, we study grounded neural language models. Literature in psychology informs us that spatial cognition involves different aspects of knowledge that include visual perception and human interaction with the world. This makes spatial descriptions a compelling case for the study of how spatial language is grounded in different kinds of knowledge. In seven studies, we investigate what and how neural language mod... more
ISBN: 978-91-7833-917-4
978-91-7833-916-7
URI: http://hdl.handle.net/2077/64095
Appears in Collections:Doctoral Theses from University of Gothenburg / Doktorsavhandlingar från Göteborgs universitet
Doctoral Theses / Doktorsavhandlingar Institutionen för filosofi, lingvistik och vetenskapsteori

 

 

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