Papers with neural network potentials

1 papers
Neural Factor Graph Models for Cross-lingual Morphological Tagging (P18-1)

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Challenge: Existing approaches to morphological tagging are limited by the assumption that tag sets overlap . a limited amount of data is available for most languages to learn these morphology taggers.
Approach: They propose a method for cross-lingual morphological tagging that relaxes this assumption . they use factorial conditional random fields with neural network potentials to smooth over superficial differences in the surface forms .
Outcome: The proposed model can smooth over superficial differences in the surface forms and generate unseen or rare tag sets.

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