Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning Bilingual Word Embeddings Using Lexical Definitions   Bilingual word embeddings, which representlexicons of different languages in
a shared em-bedding space, are essential for supporting se-mantic and knowledge
transfers in a variety ofcross-lingual NLP tasks. Existing approachesto
training bilingual word embeddings requireoften require pre-defined seed
lexicons that areexpensive to obtain, or parallel sentences thatcomprise coarse
and noisy alignment. In con-trast, we propose BilLex that leverages pub-licly
available lexical definitions for bilingualword embedding learning. Without the
needof predefined seed lexicons, BilLex comprisesa novel word pairing strategy
to automati-cally identify and propagate the precise fine-grained word
alignment from lexical defini-tions. We evaluate BilLex in word-level
andsentence-level translation tasks, which seek tofind the cross-lingual
counterparts of wordsand sentences respectively.BilLex signifi-cantly
outperforms previous embedding meth-ods on both tasks.

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The categories of this paper are: math-ph
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The categories of this paper are: q-alg
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The categories of this paper are: q-fin
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The categories of this paper are: nlin
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The categories of this paper are: patt-sol
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The categories of this paper are: quant-ph
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The categories of this paper are: nucl-th
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The categories of this paper are: hep-lat
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The categories of this paper are: funct-an
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The categories of this paper are: alg-geom
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The categories of this paper are: solv-int
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The categories of this paper are: mtrl-th
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The categories of this paper are: hep-ph
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The categories of this paper are: nucl-ex
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The categories of this paper are: eess
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The categories of this paper are: comp-gas