Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: ECMG: Exemplar-based Commit Message Generation   Commit messages concisely describe the content of code diffs (i.e., code
changes) and the intent behind them. Recently, many approaches have been
proposed to generate commit messages automatically. The information
retrieval-based methods reuse the commit messages of similar code diffs, while
the neural-based methods learn the semantic connection between code diffs and
commit messages. However, the reused commit messages might not accurately
describe the content/intent of code diffs and neural-based methods tend to
generate high-frequent and repetitive tokens in the corpus. In this paper, we
combine the advantages of the two technical routes and propose a novel
exemplar-based neural commit message generation model, which treats the similar
commit message as an exemplar and leverages it to guide the neural network
model to generate an accurate commit message. We perform extensive experiments
and the results confirm the effectiveness of our model.

25
The categories of this paper are: patt-sol
22
The categories of this paper are: chao-dyn
19
The categories of this paper are: eess
10
The categories of this paper are: q-bio
5
The categories of this paper are: gr-qc
36
The categories of this paper are: cmp-lg
35
The categories of this paper are: mtrl-th
15
The categories of this paper are: nucl-ex
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The categories of this paper are: alg-geom
32
The categories of this paper are: atom-ph
17
The categories of this paper are: q-fin
7
The categories of this paper are: hep-th
29
The categories of this paper are: funct-an
16
The categories of this paper are: stat
3
The categories of this paper are: physics
31
The categories of this paper are: ao-sci