Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning Articulated Motion Models from Visual and Lingual Signals   In order for robots to operate effectively in homes and workplaces, they must
be able to manipulate the articulated objects common within environments built
for and by humans. Previous work learns kinematic models that prescribe this
manipulation from visual demonstrations. Lingual signals, such as natural
language descriptions and instructions, offer a complementary means of
conveying knowledge of such manipulation models and are suitable to a wide
range of interactions (e.g., remote manipulation). In this paper, we present a
multimodal learning framework that incorporates both visual and lingual
information to estimate the structure and parameters that define kinematic
models of articulated objects. The visual signal takes the form of an RGB-D
image stream that opportunistically captures object motion in an unprepared
scene. Accompanying natural language descriptions of the motion constitute the
lingual signal. We present a probabilistic language model that uses word
embeddings to associate lingual verbs with their corresponding kinematic
structures. By exploiting the complementary nature of the visual and lingual
input, our method infers correct kinematic structures for various multiple-part
objects on which the previous state-of-the-art, visual-only system fails. We
evaluate our multimodal learning framework on a dataset comprised of a variety
of household objects, and demonstrate a 36% improvement in model accuracy over
the vision-only baseline.

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The categories of this paper are: hep-th
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The categories of this paper are: chao-dyn
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The categories of this paper are: cmp-lg
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The categories of this paper are: physics
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The categories of this paper are: stat
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The categories of this paper are: astro-ph
27
The categories of this paper are: comp-gas
23
The categories of this paper are: solv-int
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The categories of this paper are: alg-geom
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The categories of this paper are: bayes-an
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The categories of this paper are: econ
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The categories of this paper are: cond-mat
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The categories of this paper are: hep-ex
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The categories of this paper are: nucl-ex
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The categories of this paper are: chem-ph
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The categories of this paper are: mtrl-th