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        <title>Learning Visually Grounded Sentence Representations</title>
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        <namePart type="given">Douwe</namePart>
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        <namePart type="given">Maximilian</namePart>
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            <namePart type="given">Marilyn</namePart>
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    <abstract>We investigate grounded sentence representations, where we train a sentence encoder to predict the image features of a given caption—i.e., we try to “imagine” how a sentence would be depicted visually—and use the resultant features as sentence representations. We examine the quality of the learned representations on a variety of standard sentence representation quality benchmarks, showing improved performance for grounded models over non-grounded ones. In addition, we thoroughly analyze the extent to which grounding contributes to improved performance, and show that the system also learns improved word embeddings.</abstract>
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%0 Conference Proceedings
%T Learning Visually Grounded Sentence Representations
%A Kiela, Douwe
%A Conneau, Alexis
%A Jabri, Allan
%A Nickel, Maximilian
%Y Walker, Marilyn
%Y Ji, Heng
%Y Stent, Amanda
%S Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F kiela-etal-2018-learning
%X We investigate grounded sentence representations, where we train a sentence encoder to predict the image features of a given caption—i.e., we try to “imagine” how a sentence would be depicted visually—and use the resultant features as sentence representations. We examine the quality of the learned representations on a variety of standard sentence representation quality benchmarks, showing improved performance for grounded models over non-grounded ones. In addition, we thoroughly analyze the extent to which grounding contributes to improved performance, and show that the system also learns improved word embeddings.
%R 10.18653/v1/N18-1038
%U https://aclanthology.org/N18-1038
%U https://doi.org/10.18653/v1/N18-1038
%P 408-418

Markdown (Informal)

[Learning Visually Grounded Sentence Representations](https://aclanthology.org/N18-1038) (Kiela et al., NAACL 2018)

• Learning Visually Grounded Sentence Representations (Kiela et al., NAACL 2018)

ACL

• Douwe Kiela, Alexis Conneau, Allan Jabri, and Maximilian Nickel. 2018. Learning Visually Grounded Sentence Representations. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pages 408–418, New Orleans, Louisiana. Association for Computational Linguistics.