Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Example-Based Named Entity Recognition   We present a novel approach to named entity recognition (NER) in the presence
of scarce data that we call example-based NER. Our train-free few-shot learning
approach takes inspiration from question-answering to identify entity spans in
a new and unseen domain. In comparison with the current state-of-the-art, the
proposed method performs significantly better, especially when using a low
number of support examples.

10
The categories of this paper are: q-bio
27
The categories of this paper are: comp-gas
0
The categories of this paper are: hep-ph
26
The categories of this paper are: bayes-an
30
The categories of this paper are: q-alg
15
The categories of this paper are: nucl-ex
3
The categories of this paper are: physics
4
The categories of this paper are: cond-mat
19
The categories of this paper are: eess
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The categories of this paper are: nlin
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The categories of this paper are: funct-an
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The categories of this paper are: nucl-th
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The categories of this paper are: gr-qc
14
The categories of this paper are: math-ph
16
The categories of this paper are: stat
35
The categories of this paper are: mtrl-th