Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: DOTIN: Dropping Task-Irrelevant Nodes for GNNs   Scalability is an important consideration for deep graph neural networks.
Inspired by the conventional pooling layers in CNNs, many recent graph learning
approaches have introduced the pooling strategy to reduce the size of graphs
for learning, such that the scalability and efficiency can be improved.
However, these pooling-based methods are mainly tailored to a single
graph-level task and pay more attention to local information, limiting their
performance in multi-task settings which often require task-specific global
information. In this paper, departure from these pooling-based efforts, we
design a new approach called DOTIN (\underline{D}r\underline{o}pping
\underline{T}ask-\underline{I}rrelevant \underline{N}odes) to reduce the size
of graphs. Specifically, by introducing $K$ learnable virtual nodes to
represent the graph embeddings targeted to $K$ different graph-level tasks,
respectively, up to 90\% raw nodes with low attentiveness with an attention
model -- a transformer in this paper, can be adaptively dropped without notable
performance decreasing. Achieving almost the same accuracy, our method speeds
up GAT by about 50\% on graph-level tasks including graph classification and
graph edit distance (GED) with about 60\% less memory, on D\&D dataset. Code
will be made publicly available in https://github.com/Sherrylone/DOTIN.

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The categories of this paper are: alg-geom
3
The categories of this paper are: physics
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The categories of this paper are: adap-org
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The categories of this paper are: econ
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The categories of this paper are: hep-th
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The categories of this paper are: ao-sci
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The categories of this paper are: hep-ph
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The categories of this paper are: cond-mat
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The categories of this paper are: hep-ex
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The categories of this paper are: math
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The categories of this paper are: mtrl-th
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The categories of this paper are: bayes-an
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The categories of this paper are: nucl-ex
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The categories of this paper are: stat
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The categories of this paper are: comp-gas
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The categories of this paper are: q-bio