Dimitar Shterionov
Title
Cited by
Cited by
Year
Inference and learning in probabilistic logic programs using weighted Boolean formulas
D Fierens, G Van den Broeck, J Renkens, D Shterionov, B Gutmann, ...
Theory and Practice of Logic Programming 15 (3), 358-401, 2015
2772015
Multi-domain neural machine translation
S Tars, M Fishel
arXiv preprint arXiv:1805.02282, 2018
1442018
Lost in translation: loss and decay of linguistic richness in machine translation
E Vanmassenhove, D Shterionov, A Way
European Association for Machine Translation 1, 2019
442019
Human versus automatic quality evaluation of NMT and PBSMT
D Shterionov, R Superbo, P Nagle, L Casanellas, T O’dowd, A Way
Machine Translation 32 (3), 217-235, 2018
432018
Empirical evaluation of NMT and PBSMT quality for large-scale translation production
D Shterionov, P Nagle, L Casanellas, R Superbo, T O'Dowd
20th Annual Conference of the European Association for Machine Translation …, 2017
252017
Combining SMT and NMT back-translated data for efficient NMT
A Poncelas, M Popovic, D Shterionov, GMDB Wenniger, A Way
arXiv preprint arXiv:1909.03750, 2019
122019
ProbLog2: From probabilistic programming to statistical relational learning
J Renkens, D Shterionov, G Van den Broeck, J Vlasselaer, D Fierens, ...
Proceedings of the NIPS Probabilistic Programming Workshop, 2012
112012
DNF sampling for ProbLog inference
DS Shterionov, A Kimmig, T Mantadelis, G Janssens
arXiv preprint arXiv:1009.3798, 2010
112010
A review of the state-of-the-art in automatic post-editing
F do Carmo, D Shterionov, J Moorkens, J Wagner, M Hossari, E Paquin, ...
Machine Translation 35 (2), 101-143, 2021
92021
The most probable explanation for probabilistic logic programs with annotated disjunctions
D Shterionov, J Renkens, J Vlasselaer, A Kimmig, W Meert, G Janssens
Inductive Logic Programming, 139-153, 2015
92015
Data acquisition and modeling for learning and reasoning in probabilistic logic environment
D Shterionov, G Janssens
Proceedings of the 15th Portuguese Conference on Artificial Intelligence …, 2011
82011
Implementation and performance of probabilistic inference pipelines
D Shterionov, G Janssens
International Symposium on Practical Aspects of Declarative Languages, 90-104, 2015
72015
Machine translationese: Effects of algorithmic bias on linguistic complexity in machine translation
E Vanmassenhove, D Shterionov, M Gwilliam
arXiv preprint arXiv:2102.00287, 2021
62021
Selecting backtranslated data from multiple sources for improved neural machine translation
X Soto, D Shterionov, A Poncelas, A Way
arXiv preprint arXiv:2005.00308, 2020
62020
Zero-shot translation for Indian languages with sparse data
G Mattoni, P Nagle, C Collantes, D Shterionov
Proceedings of the 16th machine translation summit (MTSummit 2017) 2, 1-10, 2017
52017
Compacting boolean formulae for inference in probabilistic logic programming
T Mantadelis, D Shterionov, G Janssens
International Conference on Logic Programming and Nonmonotonic Reasoning …, 2015
52015
A roadmap to neural automatic post-editing: an empirical approach
D Shterionov, F do Carmo, J Moorkens, M Hossari, J Wagner, E Paquin, ...
Machine Translation 34 (2), 67-96, 2020
32020
Crucial components in probabilistic inference pipelines
D Shterionov, G Janssens
Proceedings of the 30th Annual ACM Symposium on Applied Computing, 1887-1889, 2015
32015
APE through neural and statistical MT with augmented data. ADAPT/DCU submission to the WMT 2019 APE shared task
D Shterionov, J Wagner, F Do Carmo
Proceedings of the Fourth Conference on Machine Translation (Volume 3 …, 2019
22019
ABI neural ensemble model for gender prediction adapt Bar-ilan submission for the Clin29 shared task on gender prediction
E Vanmassenhove, A Moryossef, A Poncelas, A Way, D Shterionov
arXiv preprint arXiv:1902.08856, 2019
22019
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Articles 1–20