Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Distributional Modeling on a Diet: One-shot Word Learning from Text Only   We test whether distributional models can do one-shot learning of
definitional properties from text only. Using Bayesian models, we find that
first learning overarching structure in the known data, regularities in textual
contexts and in properties, helps one-shot learning, and that individual
context items can be highly informative. Our experiments show that our model
can learn properties from a single exposure when given an informative
utterance.

21
The categories of this paper are: adap-org
12
The categories of this paper are: nucl-th
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The categories of this paper are: quant-ph
11
The categories of this paper are: hep-lat
0
The categories of this paper are: hep-ph
10
The categories of this paper are: q-bio
26
The categories of this paper are: bayes-an
31
The categories of this paper are: ao-sci
27
The categories of this paper are: comp-gas
2
The categories of this paper are: math
16
The categories of this paper are: stat
34
The categories of this paper are: chem-ph
15
The categories of this paper are: nucl-ex
25
The categories of this paper are: patt-sol
32
The categories of this paper are: atom-ph
6
The categories of this paper are: astro-ph