Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Mapping Natural Language Commands to Web Elements   The web provides a rich, open-domain environment with textual, structural,
and spatial properties. We propose a new task for grounding language in this
environment: given a natural language command (e.g., "click on the second
article"), choose the correct element on the web page (e.g., a hyperlink or
text box). We collected a dataset of over 50,000 commands that capture various
phenomena such as functional references (e.g. "find who made this site"),
relational reasoning (e.g. "article by john"), and visual reasoning (e.g.
"top-most article"). We also implemented and analyzed three baseline models
that capture different phenomena present in the dataset.

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The categories of this paper are: solv-int
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The categories of this paper are: chao-dyn
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The categories of this paper are: hep-th
2
The categories of this paper are: math
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The categories of this paper are: dg-ga
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The categories of this paper are: nlin
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The categories of this paper are: funct-an
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The categories of this paper are: physics
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The categories of this paper are: hep-lat
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The categories of this paper are: comp-gas
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The categories of this paper are: eess
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The categories of this paper are: patt-sol
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The categories of this paper are: stat
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The categories of this paper are: adap-org
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The categories of this paper are: ao-sci
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The categories of this paper are: plasm-ph