Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: EDITOR: an Edit-Based Transformer with Repositioning for Neural Machine
  Translation with Soft Lexical Constraints   We introduce an Edit-Based Transformer with Repositioning (EDITOR), which
makes sequence generation flexible by seamlessly allowing users to specify
preferences in output lexical choice. Building on recent models for
non-autoregressive sequence generation (Gu et al., 2019), EDITOR generates new
sequences by iteratively editing hypotheses. It relies on a novel reposition
operation designed to disentangle lexical choice from word positioning
decisions, while enabling efficient oracles for imitation learning and parallel
edits at decoding time. Empirically, EDITOR uses soft lexical constraints more
effectively than the Levenshtein Transformer (Gu et al., 2019) while speeding
up decoding dramatically compared to constrained beam search (Post and Vilar,
2018). EDITOR also achieves comparable or better translation quality with
faster decoding speed than the Levenshtein Transformer on standard
Romanian-English, English-German, and English-Japanese machine translation
tasks.

30
The categories of this paper are: q-alg
12
The categories of this paper are: nucl-th
11
The categories of this paper are: hep-lat
28
The categories of this paper are: alg-geom
9
The categories of this paper are: nlin
22
The categories of this paper are: chao-dyn
34
The categories of this paper are: chem-ph
35
The categories of this paper are: mtrl-th
20
The categories of this paper are: acc-phys
13
The categories of this paper are: quant-ph
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The categories of this paper are: bayes-an
37
The categories of this paper are: supr-con
3
The categories of this paper are: physics
25
The categories of this paper are: patt-sol
7
The categories of this paper are: hep-th
10
The categories of this paper are: q-bio