Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Cross-relation Cross-bag Attention for Distantly-supervised Relation
  Extraction   Distant supervision leverages knowledge bases to automatically label
instances, thus allowing us to train relation extractor without human
annotations. However, the generated training data typically contain massive
noise, and may result in poor performances with the vanilla supervised
learning. In this paper, we propose to conduct multi-instance learning with a
novel Cross-relation Cross-bag Selective Attention (C$^2$SA), which leads to
noise-robust training for distant supervised relation extractor. Specifically,
we employ the sentence-level selective attention to reduce the effect of noisy
or mismatched sentences, while the correlation among relations were captured to
improve the quality of attention weights. Moreover, instead of treating all
entity-pairs equally, we try to pay more attention to entity-pairs with a
higher quality. Similarly, we adopt the selective attention mechanism to
achieve this goal. Experiments with two types of relation extractor demonstrate
the superiority of the proposed approach over the state-of-the-art, while
further ablation studies verify our intuitions and demonstrate the
effectiveness of our proposed two techniques.

34
The categories of this paper are: chem-ph
0
The categories of this paper are: hep-ph
17
The categories of this paper are: q-fin
31
The categories of this paper are: ao-sci
26
The categories of this paper are: bayes-an
12
The categories of this paper are: nucl-th
5
The categories of this paper are: gr-qc
21
The categories of this paper are: adap-org
19
The categories of this paper are: eess
13
The categories of this paper are: quant-ph
14
The categories of this paper are: math-ph
33
The categories of this paper are: plasm-ph
35
The categories of this paper are: mtrl-th
15
The categories of this paper are: nucl-ex
7
The categories of this paper are: hep-th
23
The categories of this paper are: solv-int