Rudolf Rosa

Natural Language Processing · 2011–2019

A researcher in the Science corpus: 11 papers; trusts 81 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Natural Language Processing — 100 citations into it; #3,876 of 5,688 by trust here, #2,695 by citations
• Artificial Intelligence — 77 citations into it; #20,073 of 35,345 by trust here, #15,542 by citations
• Evaluation & Benchmarks — 28 citations into it; #2,399 of 3,147 by trust here, #1,856 by citations
• Representation & Self-Supervised Learning — 12 citations into it
• Machine Translation — 11 citations into it
• Computer Vision and Pattern Recognition — 9 citations into it; #16,502 of 21,575 by trust here, #20,756 by citations
• Optimization & Training — 6 citations into it
• Large Language Models — 5 citations into it

Whom Rudolf Rosa trusts overall

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

1. Philipp Koehn
2. Franz Joseph Och
3. Martin Popel
4. Christopher D. Manning
5. Zdenek Zabokrtský
6. Ondrej Bojar
7. Yonatan Belinkov
8. Mitchell P. Marcus
9. Andreas Stolcke
10. Yoshua Bengio

Who trusts Rudolf Rosa overall

1. Zhiyong Wu
2. Ondrej Bojar
3. Ales Tamchyna
4. Yun Chen
5. Yonatan Belinkov
6. Roman Sudarikov
7. Taeuk Kim
8. Ondrej Dusek
9. B. Kao
10. K. McKeown

Papers from Rudolf Rosa's perspective

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

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

Their papers

• Extracting Syntactic Trees from Transformer Encoder Self-Attentions (2018) — 37 citations
• CUNI in WMT14: Chimera Still Awaits Bellerophon (2014) — 11 citations
• Adaptation of machine translation for multilingual information retrieval in the medical domain (2014) — 50 citations
• From Balustrades to Pierre Vinken: Looking for Syntax in Transformer Self-Attentions (2019) — 57 citations
• Inducing Syntactic Trees from BERT Representations (2019) — 24 citations
• Universal Dependencies 2.1 (2017) — 425 citations
• Dictionary-based Domain Adaptation of MT Systems without Retraining (2016) — 4 citations
• New Language Pairs in TectoMT (2015) — 15 citations
• Machine Translation of Medical Texts in the Khresmoi Project (2014) — 26 citations
• Chimera – Three Heads for English-to-Czech Translation (2013) — 28 citations
• Two-step translation with grammatical post-processing (2011) — 40 citations