Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: DeepVar: An End-to-End Deep Learning Approach for Genomic Variant
  Recognition in Biomedical Literature   We consider the problem of Named Entity Recognition (NER) on biomedical
scientific literature, and more specifically the genomic variants recognition
in this work. Significant success has been achieved for NER on canonical tasks
in recent years where large data sets are generally available. However, it
remains a challenging problem on many domain-specific areas, especially the
domains where only small gold annotations can be obtained. In addition, genomic
variant entities exhibit diverse linguistic heterogeneity, differing much from
those that have been characterized in existing canonical NER tasks. The
state-of-the-art machine learning approaches in such tasks heavily rely on
arduous feature engineering to characterize those unique patterns. In this
work, we present the first successful end-to-end deep learning approach to
bridge the gap between generic NER algorithms and low-resource applications
through genomic variants recognition. Our proposed model can result in
promising performance without any hand-crafted features or post-processing
rules. Our extensive experiments and results may shed light on other similar
low-resource NER applications.

14
The categories of this paper are: math-ph
4
The categories of this paper are: cond-mat
8
The categories of this paper are: hep-ex
0
The categories of this paper are: hep-ph
27
The categories of this paper are: comp-gas
34
The categories of this paper are: chem-ph
33
The categories of this paper are: plasm-ph
13
The categories of this paper are: quant-ph
31
The categories of this paper are: ao-sci
11
The categories of this paper are: hep-lat
23
The categories of this paper are: solv-int
16
The categories of this paper are: stat
20
The categories of this paper are: acc-phys
21
The categories of this paper are: adap-org
37
The categories of this paper are: supr-con
32
The categories of this paper are: atom-ph