Dimitar Shterionov
Cited by
Cited by
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
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
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
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
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
Machine translationese: Effects of algorithmic bias on linguistic complexity in machine translation
E Vanmassenhove, D Shterionov, M Gwilliam
arXiv preprint arXiv:2102.00287, 2021
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
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
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
DNF sampling for ProbLog inference
DS Shterionov, A Kimmig, T Mantadelis, G Janssens
arXiv preprint arXiv:1009.3798, 2010
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
A roadmap to neural automatic post-editing: an empirical approach
D Shterionov, F Carmo, J Moorkens, M Hossari, J Wagner, E Paquin, ...
Machine Translation 34 (2), 67-96, 2020
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
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
Implementation and performance of probabilistic inference pipelines
D Shterionov, G Janssens
International Symposium on Practical Aspects of Declarative Languages, 90-104, 2015
When less is more in neural quality estimation of machine translation. An industry case study
D Shterionov, F do Carmo, J Moorkens, E Paquin, D Schmidtke, D Groves, ...
European Association for Machine Translation 2, 2019
Compacting boolean formulae for inference in probabilistic logic programming
T Mantadelis, D Shterionov, G Janssens
International Conference on Logic Programming and Nonmonotonic Reasoning …, 2015
NeuTral Rewriter: A Rule-Based and Neural Approach to Automatic Rewriting into Gender-Neutral Alternatives
E Vanmassenhove, C Emmery, D Shterionov
arXiv preprint arXiv:2109.06105, 2021
The signon project: a sign language translation framework
D Shterionov, V Vandeghinste, H Saggion, J Blat, M De Coster, J Dambre, ...
31st Meeting of Computational Linguistics in The Netherlands, 2021
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
The system can't perform the operation now. Try again later.
Articles 1–20