| Sockeye: A Toolkit for Neural Machine Translation F Hieber, T Domhan, M Denkowski, D Vilar, A Sokolov, A Clifton, M Post arXiv preprint arXiv:1712.05690, 2017 | 239 | 2017 |
| Using target-side monolingual data for neural machine translation through multi-task learning T Domhan, F Hieber | 104 | 2017 |
| The sockeye neural machine translation toolkit at AMTA 2018 F Hieber, T Domhan, M Denkowski, D Vilar, A Sokolov, A Clifton, M Post Proceedings of the 13th Conference of the Association for Machine …, 2018 | 68 | 2018 |
| Twitter translation using translation-based cross-lingual retrieval L Jehl, F Hieber, S Riezler Proceedings of the Seventh Workshop on Statistical Machine Translation, 410-421, 2012 | 60 | 2012 |
| Learning Translational and Knowledge-based Similarities from Relevance Rankings for Cross-Language Retrieval S Schamoni, F Hieber, A Sokolov, S Riezler | 37 | 2014 |
| The Sockeye 2 Neural Machine Translation Toolkit at AMTA 2020 T Domhan, M Denkowski, D Vilar, X Niu, F Hieber, K Heafield arXiv preprint arXiv:2008.04885, 2020 | 33 | 2020 |
| Improved answer ranking in social question-answering portals F Hieber, S Riezler Proceedings of the 3rd international workshop on Search and mining user …, 2011 | 32 | 2011 |
| Efficient online domain adaptation F Hieber, J May US Patent 9,213,694, 2015 | 25 | 2015 |
| Learning to Translate Queries for CLIR A Sokolov, F Hieber, S Riezler SIGIR, 2014 | 21 | 2014 |
| Boosting cross-language retrieval by learning bilingual phrase associations from relevance rankings A Sokolov, L Jehl, F Hieber, S Riezler Proceedings of the Conference on Empirical Methods in Natural Language …, 2013 | 21 | 2013 |
| Bag-of-words forced decoding for cross-lingual information retrieval F Hieber, S Riezler Proceedings of the 2015 Conference of the North American Chapter of the …, 2015 | 20 | 2015 |
| Artificial intelligence system using phrase tables to evaluate and improve neural network based machine translation H Fuerstenau, F Hieber US Patent 10,747,962, 2020 | 19 | 2020 |
| Sockeye 3: Fast neural machine translation with pytorch F Hieber, M Denkowski, T Domhan, BD Barros, CD Ye, X Niu, C Hoang, ... arXiv preprint arXiv:2207.05851, 2022 | 14 | 2022 |
| Generating LTAG grammars from a lexicon/ontology interface C Unger, F Hieber, P Cimiano Proceedings of the 10th International Workshop on Tree Adjoining Grammar and …, 2010 | 14 | 2010 |
| The Devil is in the Details: On the Pitfalls of Vocabulary Selection in Neural Machine Translation T Domhan, E Hasler, K Tran, S Trenous, B Byrne, F Hieber arXiv preprint arXiv:2205.06618, 2022 | 9 | 2022 |
| Analyzing the Use of Influence Functions for Instance-Specific Data Filtering in Neural Machine Translation TK Lam, E Hasler, F Hieber arXiv preprint arXiv:2210.13281, 2022 | 6 | 2022 |
| Improving the Quality Trade-Off for Neural Machine Translation Multi-Domain Adaptation E Hasler, T Domhan, J Trénous, KM Tran, B Byrne, F Hieber Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021 | 6 | 2021 |
| Separating translation correction post-edits from content improvement post-edits in machine translated content H Fuerstenau, F Hieber US Patent 10,248,651, 2019 | 6 | 2019 |
| Artificial intelligence system using phrase tables to evaluate and improve neural network based machine translation H Fuerstenau, F Hieber US Patent 11,328,129, 2022 | 3 | 2022 |
| Translation-based Ranking in Cross-Language Information Retrieval F Hieber | 3 | 2015 |
Tobias DomhanMachine Learning Scientist, AmazonVerified email at amazon.com
