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D-Index & Metrics

Computer Science

D-Index
50
Citations
19413
World Ranking
5480
National Ranking
113

Overview

Rico Sennrich is affiliated with the University of Zurich in Switzerland. Their research primarily focuses on computer science and its subfields, with a strong emphasis on artificial intelligence, including applications in computer vision and pattern recognition, human-computer interaction, developmental and educational psychology, and language and linguistics.

Their work covers several main topics, including natural language processing techniques, topic modeling, multimodal machine learning applications, text readability and simplification, speech recognition and synthesis, explainable artificial intelligence (XAI), and sentiment analysis and opinion mining.

Recent papers authored or co-authored by Rico Sennrich include:

  • Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation, 2020, arXiv (Cornell University)
  • A Set of Recommendations for Assessing Human-Machine Parity in Language Translation, 2020, Zurich Open Repository and Archive (University of Zurich)
  • Share or Not? Learning to Schedule Language-Specific Capacity for Multilingual Translation, 2021, Zurich Open Repository and Archive (University of Zurich)
  • X-Stance: A Multilingual Multi-Target Dataset for Stance Detection, 2020, arXiv (Cornell University)
  • Domain robustness in neural machine translation, 2020, Zurich Open Repository and Archive (University of Zurich)

Sennrich frequently collaborates with several co-authors, including Jannis Vamvas, Ivan Titov, Biao Zhang, Chantal Amrhein, and Annette Rios.

The primary venues where their work has been published include:

  • arXiv (Cornell University)
  • Zurich Open Repository and Archive (University of Zurich)
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • Zenodo (CERN European Organization for Nuclear Research)
  • Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Best Publications

  • Neural Machine Translation of Rare Words with Subword Units

    Rico Sennrich;Barry Haddow;Alexandra Birch

  • Improving Neural Machine Translation Models with Monolingual Data

    Rico Sennrich;Barry Haddow;Alexandra Birch

  • Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned

    Elena Voita;Elena Voita;David Talbot;Fedor Moiseev;Fedor Moiseev;Rico Sennrich

  • Edinburgh Neural Machine Translation Systems for WMT 16

    Rico Sennrich;Barry Haddow;Alexandra Birch

  • Linguistic Input Features Improve Neural Machine Translation

    Rico Sennrich;Barry Haddow

  • Nematus: a Toolkit for Neural Machine Translation

    Rico Sennrich;Orhan Firat;Kyunghyun Cho;Alexandra Birch

  • Context-Aware Neural Machine Translation Learns Anaphora Resolution

    Elena Voita;Elena Voita;Pavel Serdyukov;Rico Sennrich;Rico Sennrich;Ivan Titov;Ivan Titov

  • Controlling Politeness in Neural Machine Translation via Side Constraints

    Rico Sennrich;Barry Haddow;Alexandra Birch

  • Why Self-Attention? A Targeted Evaluation of Neural Machine Translation Architectures

    Gongbo Tang;Matthias Muller;Annette Rios;Rico Sennrich

  • Has Machine Translation Achieved Human Parity? A Case for Document-level Evaluation

    Samuel Läubli;Rico Sennrich;Martin Volk

  • Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation

    Biao Zhang;Philip Williams;Ivan Titov;Rico Sennrich

  • Paraphrasing Revisited with Neural Machine Translation

    Jonathan Mallinson;Rico Sennrich;Mirella Lapata

  • Revisiting Low-Resource Neural Machine Translation: A Case Study

    Rico Sennrich;Biao Zhang

  • Evaluating Discourse Phenomena in Neural Machine Translation

    Rachel Bawden;Rico Sennrich;Alexandra Birch;Barry Haddow

  • When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical Cohesion

    Elena Voita;Elena Voita;Rico Sennrich;Ivan Titov

  • The University of Edinburgh's Neural MT Systems for WMT17

    Rico Sennrich;Alexandra Birch;Anna Currey;Ulrich Germann

  • Perplexity Minimization for Translation Model Domain Adaptation in Statistical Machine Translation

    Rico Sennrich

  • The Bottom-up Evolution of Representations in the Transformer: A Study with Machine Translation and Language Modeling Objectives

    Elena Voita;Elena Voita;Rico Sennrich;Ivan Titov

  • How Grammatical is Character-level Neural Machine Translation? Assessing MT Quality with Contrastive Translation Pairs

    Rico Sennrich

  • Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics

    Rico Sennrich

  • Synthesis Lectures on Human Language Technologies

    Philip Williams;Rico Sennrich;Matt Post;Philipp Koehn

Frequent Co-Authors

Barry Haddow
Barry Haddow University of Edinburgh
Ivan Titov
Ivan Titov University of Edinburgh
Joakim Nivre
Joakim Nivre Uppsala University
Philipp Koehn
Philipp Koehn Johns Hopkins University
Andy Way
Andy Way Dublin City University
Alex Waibel
Alex Waibel Carnegie Mellon University
Mirella Lapata
Mirella Lapata University of Edinburgh
Ondrej Bojar
Ondrej Bojar Charles University
Frank Keller
Frank Keller University of Edinburgh
Graham Neubig
Graham Neubig Carnegie Mellon University

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