Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Resource-Free Evaluation Metric for Cross-Lingual Word Embeddings
  Based on Graph Modularity   Cross-lingual word embeddings encode the meaning of words from different
languages into a shared low-dimensional space. An important requirement for
many downstream tasks is that word similarity should be independent of language
- i.e., word vectors within one language should not be more similar to each
other than to words in another language. We measure this characteristic using
modularity, a network measurement that measures the strength of clusters in a
graph. Modularity has a moderate to strong correlation with three downstream
tasks, even though modularity is based only on the structure of embeddings and
does not require any external resources. We show through experiments that
modularity can serve as an intrinsic validation metric to improve unsupervised
cross-lingual word embeddings, particularly on distant language pairs in
low-resource settings.

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The categories of this paper are: math
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The categories of this paper are: econ
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The categories of this paper are: comp-gas
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The categories of this paper are: hep-th
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The categories of this paper are: alg-geom
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The categories of this paper are: nucl-ex
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The categories of this paper are: hep-lat
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The categories of this paper are: solv-int
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The categories of this paper are: stat
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The categories of this paper are: nlin
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The categories of this paper are: quant-ph
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The categories of this paper are: gr-qc
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The categories of this paper are: funct-an
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The categories of this paper are: q-fin
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The categories of this paper are: astro-ph
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The categories of this paper are: plasm-ph