tune-n-distill/CITATION.cff at main · transducens/tune-n-distill · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: tune-n-distill
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Aarón
    family-names: Galiano-Jiménez
    email: aaron.galiano@ua.es
    affiliation: >-
      Universitat d'Alacant, Transducens research group,
      Spain
    orcid: 'https://orcid.org/0000-0002-8107-1411'
  - given-names: Felipe
    family-names: Sánchez-Martínez
    email: fsanchez@dlsi.ua.es
    affiliation: >-
      Universitat d'Alacant, Transducens research group,
      Spain
    orcid: 'https://orcid.org/0000-0002-2295-2630'
  - given-names: Víctor M.
    family-names: Sánchez-Cartagena
    affiliation: >-
      Universitat d'Alacant, Transducens research group,
      Spain
    email: vmsanchez@dlsi.ua.es
    orcid: 'https://orcid.org/0000-0001-9600-6885'
  - given-names: Juan Antonio
    family-names: Pérez-Ortiz
    email: japerez@ua.es
    affiliation: >-
      Universitat d'Alacant, Transducens research group,
      Spain
    orcid: 'https://orcid.org/0000-0001-7659-8908'
identifiers:
  - type: url
    value: 'https://aclanthology.org/2023.eamt-1.7/'
repository-code: 'https://github.com/transducens/tune-n-distill'
abstract: >-
  This repository contains a pipeline to tune the mBART50
  NMT pre-trained model to low-resource language pairs, and
  then distill the resulting system to obtain lightweight
  and more sustainable models. The pipeline allows training
  lightweight models for the translation between English and
  a specific low-resource language, even if mBART50 has not
  been pre-trained with the low-resource language.
keywords:
  - neural machine translation
  - fine-tuning
  - knowledge distillation
license: CC0-1.0