Explainability of Machine Translation is a scholarly construct within machine translation ethics that denotes the capacity of a translation system to provide transparent, interpretable, and human-comprehensible justifications for its output, thereby distinguishing it from opaque, black-box translation models.
6
Publications
117
Citations
21
Authors
14
Institutions
Publications per year
2017–2026
5
Parents
Publications
6
Inseq: An Interpretability Toolkit for Sequence Generation Models
Gabriele Sarti, Nils Feldhus, Ludwig Sickert et al. · 2023 · 29 citations · Full text
Evaluating Explanation Methods for Neural Machine Translation
Jierui Li, Lemao Liu, Huayang Li et al. · 2020 · 25 citations · Full text
Probabilistic explanations in translation studies
Gideon Toury · 2004 · 12 citations
1–5 of 6
Authors
21
- MF
2
h-index
- SE
2
h-index
- WZ
2
h-index
- PL
2
h-index
- SL
1
h-index
1–5 of 21
Institutions
14
University of Washington
Seattle, United States
1 h-index
4 publications
68 citations
University of Groningen
Groningen, The Netherlands
1 h-index
4 publications
116 citations
University of Electronic Science and Technology of China
Chengdu, China
1 h-index
1 publications
25 citations
The University of Melbourne
Melbourne, Australia
1 h-index
4 publications
68 citations
Harbin Institute of Technology
Harbin, China
1 h-index
1 publications
25 citations
The University of Western Australia
Perth, Australia
1 h-index
4 publications
68 citations
German Research Centre for Artificial Intelligence
Kaiserslautern, Germany
1 h-index
4 publications
116 citations
Tencent (China)
Shenzhen, China
1 h-index
4 publications
100 citations
1–8 of 14
Venues
- arXiv (Cornell University)
Repository · 2 publications · 29 citations
2
h-index
1–1