Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Adaptive Attentional Network for Few-Shot Knowledge Graph Completion   Few-shot Knowledge Graph (KG) completion is a focus of current research,
where each task aims at querying unseen facts of a relation given its few-shot
reference entity pairs. Recent attempts solve this problem by learning static
representations of entities and references, ignoring their dynamic properties,
i.e., entities may exhibit diverse roles within task relations, and references
may make different contributions to queries. This work proposes an adaptive
attentional network for few-shot KG completion by learning adaptive entity and
reference representations. Specifically, entities are modeled by an adaptive
neighbor encoder to discern their task-oriented roles, while references are
modeled by an adaptive query-aware aggregator to differentiate their
contributions. Through the attention mechanism, both entities and references
can capture their fine-grained semantic meanings, and thus render more
expressive representations. This will be more predictive for knowledge
acquisition in the few-shot scenario. Evaluation in link prediction on two
public datasets shows that our approach achieves new state-of-the-art results
with different few-shot sizes.

16
The categories of this paper are: stat
12
The categories of this paper are: nucl-th
4
The categories of this paper are: cond-mat
20
The categories of this paper are: acc-phys
22
The categories of this paper are: chao-dyn
0
The categories of this paper are: hep-ph
14
The categories of this paper are: math-ph
2
The categories of this paper are: math
13
The categories of this paper are: quant-ph
9
The categories of this paper are: nlin
24
The categories of this paper are: dg-ga
19
The categories of this paper are: eess
21
The categories of this paper are: adap-org
11
The categories of this paper are: hep-lat
27
The categories of this paper are: comp-gas
23
The categories of this paper are: solv-int