Matthias Huck

Natural Language Processing · 2013–2021

A researcher in the Science corpus: 16 papers; trusts 131 researchers and is trusted by 24 researchers here, as inferred from the citation graph.

Subfields

• Natural Language Processing — 482 citations into it; #2,175 of 5,688 by trust here, #597 by citations
• Artificial Intelligence — 426 citations into it; #7,326 of 35,345 by trust here, #1,834 by citations
• Evaluation & Benchmarks — 182 citations into it; #2,168 of 3,147 by trust here, #288 by citations
• Computer Vision and Pattern Recognition — 77 citations into it
• Machine Translation — 72 citations into it; #59 of 292 by trust here, #12 by citations
• Information Systems — 25 citations into it
• Model Architectures — 21 citations into it
• Molecular Biology — 21 citations into it; #9,822 of 17,773 by trust here, #5,350 by citations

Whom Matthias Huck trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Philipp Koehn
2. Franz Joseph Och
3. Andreas Stolcke
4. David Chiang
5. Nadir Durrani
6. Kenneth Heafield
7. Rico Sennrich
8. Michel Galley
9. Colin Cherry
10. Stanley F. Chen

Who trusts Matthias Huck overall

1. Nadir Durrani
2. Rico Sennrich
3. Barry Haddow
4. Philipp Koehn
5. Markus Freitag
6. Philip Williams
7. Ondrej Bojar
8. Hassan Sajjad
9. Alexandra Birch
10. Huda Khayrallah

Papers from Matthias Huck's perspective

Ordered by how strongly the researchers Matthias Huck trusts endorse each paper. Same corpus, a different order for every researcher.

1. Attention is All you Need (Neural Information Processing Systems)
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Long Short-Term Memory
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. ImageNet classification with deep convolutional neural networks
6. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
7. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Gradient-based learning applied to document recognition
10. Bleu: a Method for Automatic Evaluation of Machine Translation

Their papers

• Findings of the 2019 Conference on Machine Translation (WMT19) (2019) — 630 citations
• Findings of the 2016 Conference on Machine Translation (2016) — 838 citations
• Findings of the 2017 Conference on Machine Translation (WMT17) (2017) — 543 citations
• Findings of the 2015 Workshop on Statistical Machine Translation (2015) — 344 citations
• Edinburgh’s Statistical Machine Translation Systems for WMT16 (2016) — 28 citations
• Edinburgh’s Syntax-Based Systems at WMT 2015 (2014) — 20 citations
• Edinburgh’s Syntax-Based Systems at WMT 2014 (2014) — 26 citations
• The Edinburgh/JHU Phrase-based Machine Translation Systems for WMT 2015 (2015) — 20 citations
• Findings of the 2020 Conference on Machine Translation (WMT20) (2020) — 316 citations
• The Edinburgh/LMU Hierarchical Machine Translation System for WMT 2016 (2016) — 7 citations
• The QT21/HimL Combined Machine Translation System (2016) — 17 citations
• Findings of the 2021 Conference on Machine Translation (WMT21) (2021) — 244 citations
• Combined spoken language translation (2014) — 21 citations
• EU-BRIDGE MT: Combined Machine Translation (2014) — 23 citations
• Edinburgh SLT and MT system description for the IWSLT 2014 evaluation (2014) — 31 citations
• English SLT and MT system description for the IWSLT 2013 evaluation (2013) — 11 citations