Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Semantic Image Search for Robotic Applications   Generalization in robotics is one of the most important problems. New
generalization approaches use internet databases in order to solve new tasks.
Modern search engines can return a large amount of information according to a
query within milliseconds. However, not all of the returned information is task
relevant, partly due to the problem of polysemes. Here we specifically address
the problem of object generalization by using image search. We suggest a
bi-modal solution, combining visual and textual information, based on the
observation that humans use additional linguistic cues to demarcate intended
word meaning. We evaluate the quality of our approach by comparing it to human
labelled data and find that, on average, our approach leads to improved results
in comparison to Google searches, and that it can treat the problem of
polysemes.

28
The categories of this paper are: alg-geom
18
The categories of this paper are: econ
33
The categories of this paper are: plasm-ph
34
The categories of this paper are: chem-ph
13
The categories of this paper are: quant-ph
24
The categories of this paper are: dg-ga
4
The categories of this paper are: cond-mat
21
The categories of this paper are: adap-org
17
The categories of this paper are: q-fin
20
The categories of this paper are: acc-phys
32
The categories of this paper are: atom-ph
7
The categories of this paper are: hep-th
27
The categories of this paper are: comp-gas
26
The categories of this paper are: bayes-an
29
The categories of this paper are: funct-an
2
The categories of this paper are: math