Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Transformer-based Lexically Constrained Headline Generation   This paper explores a variant of automatic headline generation methods, where
a generated headline is required to include a given phrase such as a company or
a product name. Previous methods using Transformer-based models generate a
headline including a given phrase by providing the encoder with additional
information corresponding to the given phrase. However, these methods cannot
always include the phrase in the generated headline. Inspired by previous
RNN-based methods generating token sequences in backward and forward directions
from the given phrase, we propose a simple Transformer-based method that
guarantees to include the given phrase in the high-quality generated headline.
We also consider a new headline generation strategy that takes advantage of the
controllable generation order of Transformer. Our experiments with the Japanese
News Corpus demonstrate that our methods, which are guaranteed to include the
phrase in the generated headline, achieve ROUGE scores comparable to previous
Transformer-based methods. We also show that our generation strategy performs
better than previous strategies.

13
The categories of this paper are: quant-ph
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
5
The categories of this paper are: gr-qc
6
The categories of this paper are: astro-ph
3
The categories of this paper are: physics
21
The categories of this paper are: adap-org
24
The categories of this paper are: dg-ga
19
The categories of this paper are: eess
0
The categories of this paper are: hep-ph
32
The categories of this paper are: atom-ph
10
The categories of this paper are: q-bio
34
The categories of this paper are: chem-ph
16
The categories of this paper are: stat
36
The categories of this paper are: cmp-lg