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        <title>Illustrative Language Understanding: Large-Scale Visual Grounding with Image Search</title>
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        <namePart type="given">Jamie</namePart>
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            <namePart type="given">Iryna</namePart>
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            <namePart type="given">Yusuke</namePart>
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    <abstract>We introduce Picturebook, a large-scale lookup operation to ground language via ‘snapshots’ of our physical world accessed through image search. For each word in a vocabulary, we extract the top-k images from Google image search and feed the images through a convolutional network to extract a word embedding. We introduce a multimodal gating function to fuse our Picturebook embeddings with other word representations. We also introduce Inverse Picturebook, a mechanism to map a Picturebook embedding back into words. We experiment and report results across a wide range of tasks: word similarity, natural language inference, semantic relatedness, sentiment/topic classification, image-sentence ranking and machine translation. We also show that gate activations corresponding to Picturebook embeddings are highly correlated to human judgments of concreteness ratings.</abstract>
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%0 Conference Proceedings
%T Illustrative Language Understanding: Large-Scale Visual Grounding with Image Search
%A Kiros, Jamie
%A Chan, William
%A Hinton, Geoffrey
%Y Gurevych, Iryna
%Y Miyao, Yusuke
%S Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F kiros-etal-2018-illustrative
%X We introduce Picturebook, a large-scale lookup operation to ground language via ‘snapshots’ of our physical world accessed through image search. For each word in a vocabulary, we extract the top-k images from Google image search and feed the images through a convolutional network to extract a word embedding. We introduce a multimodal gating function to fuse our Picturebook embeddings with other word representations. We also introduce Inverse Picturebook, a mechanism to map a Picturebook embedding back into words. We experiment and report results across a wide range of tasks: word similarity, natural language inference, semantic relatedness, sentiment/topic classification, image-sentence ranking and machine translation. We also show that gate activations corresponding to Picturebook embeddings are highly correlated to human judgments of concreteness ratings.
%R 10.18653/v1/P18-1085
%U https://aclanthology.org/P18-1085
%U https://doi.org/10.18653/v1/P18-1085
%P 922-933

Markdown (Informal)

[Illustrative Language Understanding: Large-Scale Visual Grounding with Image Search](https://aclanthology.org/P18-1085) (Kiros et al., ACL 2018)

• Illustrative Language Understanding: Large-Scale Visual Grounding with Image Search (Kiros et al., ACL 2018)

ACL

• Jamie Kiros, William Chan, and Geoffrey Hinton. 2018. Illustrative Language Understanding: Large-Scale Visual Grounding with Image Search. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 922–933, Melbourne, Australia. Association for Computational Linguistics.