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<Paper uid="P02-1063">
  <Title>Revision Learning and its Application to Part-of-Speech Tagging</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> This paper presents a revision learning method that achieves high performance with small computational cost by combining a model with high generalization capacity and a model with small computational cost. This method uses a high capacity model to revise the output of a small cost model. We apply this method to English part-of-speech tagging and Japanese morphological analysis, and show that the method performs well.</Paragraph>
  </Section>
class="xml-element"></Paper>