Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multilingual Image Description with Neural Sequence Models   In this paper we present an approach to multi-language image description
bringing together insights from neural machine translation and neural image
description. To create a description of an image for a given target language,
our sequence generation models condition on feature vectors from the image, the
description from the source language, and/or a multimodal vector computed over
the image and a description in the source language. In image description
experiments on the IAPR-TC12 dataset of images aligned with English and German
sentences, we find significant and substantial improvements in BLEU4 and Meteor
scores for models trained over multiple languages, compared to a monolingual
baseline.

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The categories of this paper are: alg-geom
35
The categories of this paper are: mtrl-th
36
The categories of this paper are: cmp-lg
17
The categories of this paper are: q-fin
12
The categories of this paper are: nucl-th
34
The categories of this paper are: chem-ph
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The categories of this paper are: comp-gas
4
The categories of this paper are: cond-mat
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The categories of this paper are: gr-qc
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The categories of this paper are: math
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The categories of this paper are: math-ph
3
The categories of this paper are: physics
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The categories of this paper are: nlin
30
The categories of this paper are: q-alg
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The categories of this paper are: solv-int
37
The categories of this paper are: supr-con