Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multi-Level Matching and Aggregation Network for Few-Shot Relation
  Classification   This paper presents a multi-level matching and aggregation network (MLMAN)
for few-shot relation classification. Previous studies on this topic adopt
prototypical networks, which calculate the embedding vector of a query instance
and the prototype vector of each support set independently. In contrast, our
proposed MLMAN model encodes the query instance and each support set in an
interactive way by considering their matching information at both local and
instance levels. The final class prototype for each support set is obtained by
attentive aggregation over the representations of its support instances, where
the weights are calculated using the query instance. Experimental results
demonstrate the effectiveness of our proposed methods, which achieve a new
state-of-the-art performance on the FewRel dataset.

28
The categories of this paper are: alg-geom
35
The categories of this paper are: mtrl-th
9
The categories of this paper are: nlin
21
The categories of this paper are: adap-org
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The categories of this paper are: comp-gas
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The categories of this paper are: funct-an
8
The categories of this paper are: hep-ex
31
The categories of this paper are: ao-sci
17
The categories of this paper are: q-fin
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The categories of this paper are: plasm-ph
0
The categories of this paper are: hep-ph
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The categories of this paper are: chao-dyn
5
The categories of this paper are: gr-qc
13
The categories of this paper are: quant-ph
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The categories of this paper are: solv-int
18
The categories of this paper are: econ