Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Semi-Supervised Bilingual Lexicon Induction with Two-way Interaction   Semi-supervision is a promising paradigm for Bilingual Lexicon Induction
(BLI) with limited annotations. However, previous semisupervised methods do not
fully utilize the knowledge hidden in annotated and nonannotated data, which
hinders further improvement of their performance. In this paper, we propose a
new semi-supervised BLI framework to encourage the interaction between the
supervised signal and unsupervised alignment. We design two message-passing
mechanisms to transfer knowledge between annotated and non-annotated data,
named prior optimal transport and bi-directional lexicon update respectively.
Then, we perform semi-supervised learning based on a cyclic or a parallel
parameter feeding routine to update our models. Our framework is a general
framework that can incorporate any supervised and unsupervised BLI methods
based on optimal transport. Experimental results on MUSE and VecMap datasets
show significant improvement of our models. Ablation study also proves that the
two-way interaction between the supervised signal and unsupervised alignment
accounts for the gain of the overall performance. Results on distant language
pairs further illustrate the advantage and robustness of our proposed method.

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The categories of this paper are: comp-gas
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The categories of this paper are: adap-org
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The categories of this paper are: math
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The categories of this paper are: chem-ph
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The categories of this paper are: astro-ph
3
The categories of this paper are: physics
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The categories of this paper are: q-alg
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The categories of this paper are: patt-sol
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The categories of this paper are: ao-sci
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The categories of this paper are: hep-ex
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The categories of this paper are: q-bio
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The categories of this paper are: nlin
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The categories of this paper are: eess
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The categories of this paper are: quant-ph
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The categories of this paper are: econ
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The categories of this paper are: funct-an