Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Transformer-Based Approach for Joint Handwriting and Named Entity
  Recognition in Historical documents   The extraction of relevant information carried out by named entities in
handwriting documents is still a challenging task. Unlike traditional
information extraction approaches that usually face text transcription and
named entity recognition as separate subsequent tasks, we propose in this paper
an end-to-end transformer-based approach to jointly perform these two tasks.
The proposed approach operates at the paragraph level, which brings two main
benefits. First, it allows the model to avoid unrecoverable early errors due to
line segmentation. Second, it allows the model to exploit larger bi-dimensional
context information to identify the semantic categories, reaching a higher
final prediction accuracy. We also explore different training scenarios to show
their effect on the performance and we demonstrate that a two-stage learning
strategy can make the model reach a higher final prediction accuracy. As far as
we know, this work presents the first approach that adopts the transformer
networks for named entity recognition in handwritten documents. We achieve the
new state-of-the-art performance in the ICDAR 2017 Information Extraction
competition using the Esposalles database, for the complete task, even though
the proposed technique does not use any dictionaries, language modeling, or
post-processing.

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The categories of this paper are: gr-qc
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The categories of this paper are: nucl-th
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The categories of this paper are: ao-sci
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The categories of this paper are: chem-ph
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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: stat
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The categories of this paper are: adap-org
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The categories of this paper are: acc-phys
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The categories of this paper are: nucl-ex
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The categories of this paper are: nlin
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The categories of this paper are: comp-gas
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The categories of this paper are: quant-ph
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The categories of this paper are: patt-sol
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The categories of this paper are: dg-ga
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The categories of this paper are: math-ph