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D-Index & Metrics

Computer Science

D-Index
79
Citations
51902
World Ranking
1112
National Ranking
593

Overview

Philipp Koehn is affiliated with Johns Hopkins University in the United States and has contributed extensively to the field of computer science, particularly in artificial intelligence and natural language processing. Their research spans over 174 publications, with a primary focus on natural language processing techniques and topic modeling.

The scientist's work includes a variety of topics such as:

  • Natural Language Processing Techniques
  • Topic Modeling
  • Multimodal Machine Learning Applications
  • Text Readability and Simplification
  • Speech Recognition and Synthesis
  • Authorship Attribution and Profiling
  • Speech and Dialogue Systems

Philipp Koehn has written significant papers, notable among them are:

  • No Language Left Behind: Scaling Human-Centered Machine Translation, 2022, arXiv (Cornell University)
  • Scaling neural machine translation to 200 languages, 2024, Nature
  • When Does Unsupervised Machine Translation Work?, 2020, arXiv (Cornell University)
  • SimulMT to SimulST: Adapting Simultaneous Text Translation to End-to-End Simultaneous Speech Translation, 2020, arXiv (Cornell University)
  • Consistent Human Evaluation of Machine Translation across Language Pairs, 2022, arXiv (Cornell University)

The scientist has frequently coauthored research with several colleagues, including Weiting Tan, James H. Cross, Kelly Marchisio, Kenton Murray, and Francisco Guzmán. These collaborations have contributed to a cohesive body of work within their field.

Philipp Koehn's publications have appeared in a variety of respected venues. These include:

  • arXiv (Cornell University)
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • Cambridge University Press eBooks
  • Nature
  • Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

In addition to articles, they have contributed to book publications, including a title published by Cambridge University Press:

  • Neural Machine Translation, 2020

Their main fields of study revolve around computer science with a specialized emphasis on artificial intelligence. Subfields covered in their research include artificial intelligence, computer vision and pattern recognition, molecular biology, language and linguistics, and information systems.

Best Publications

  • Moses: Open Source Toolkit for Statistical Machine Translation

    Philipp Koehn;Hieu Hoang;Alexandra Birch;Chris Callison-Burch

  • Europarl: A Parallel Corpus for Statistical Machine Translation

    Philipp Koehn

  • Statistical phrase-based translation

    Philipp Koehn;Franz Josef Och;Daniel Marcu

  • Statistical Machine Translation

    Philipp Koehn

  • Statistical Significance Tests for Machine Translation Evaluation.

    Philipp Koehn

  • Six Challenges for Neural Machine Translation.

    Philipp Koehn;Rebecca Knowles

  • Abstract Meaning Representation for Sembanking

    Laura Banarescu;Claire Bonial;Shu Cai;Madalina Georgescu

  • Findings of the 2014 Workshop on Statistical Machine Translation

    Ondrej Bojar;Christian Buck;Christian Federmann;Barry Haddow

  • Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

    Adithya Renduchintala;Rebecca Knowles;Philipp Koehn;Jason Eisner

  • Findings of the 2015 Workshop on Statistical Machine Translation

    Ondřej Bojar;Rajen Chatterjee;Christian Federmann;Barry Haddow

  • Pharaoh: A Beam Search Decoder for Phrase-Based Statistical Machine Translation Models

    Philipp Koehn

  • Re-evaluating the Role of Bleu in Machine Translation Research

    Chris Callison-Burch;Miles Osborne;Philipp Koehn

  • Findings of the 2012 Workshop on Statistical Machine Translation

    Chris Callison-Burch;Philipp Koehn;Christof Monz;Matt Post

  • Findings of the 2009 Workshop on Statistical Machine Translation

    Chris Callison-Burch;Philipp Koehn;Christof Monz;Josh Schroeder

  • Findings of the 2018 Conference on Machine Translation (WMT18)

    Ondřej Bojar;Christian Federmann;Mark Fishel;Yvette Graham

  • No Language Left Behind: Scaling Human-Centered Machine Translation

    Unknown

  • Factored Translation Models

    Philipp Koehn;Hieu Hoang

  • Clause Restructuring for Statistical Machine Translation

    Michael Collins;Philipp Koehn;Ivona Kucerova

  • Findings of the 2017 Conference on Machine Translation (WMT17)

    Ondřej Bojar;Rajen Chatterjee;Christian Federmann;Yvette Graham

  • Findings of the 2016 Conference on Machine Translation

    Ondˇrej Bojar;Rajen Chatterjee;Christian Federmann;Yvette Graham

  • Statistical machine translation

    Kevin Knight;Philipp Koehn

  • Open Source Toolkit for Statistical Machine Translation: Factored Translation Models and Lattice Decoding

    Philipp Koehn;Marcello Federico;Wade Shen;Nicola Bertoldi

  • Synthesis Lectures on Human Language Technologies

    Philip Williams;Rico Sennrich;Matt Post;Philipp Koehn

  • Statistical Machine Translation: Phrase-Based Models

    Philipp Koehn

Frequent Co-Authors

Barry Haddow
Barry Haddow University of Edinburgh
Chris Callison-Burch
Chris Callison-Burch University of Pennsylvania
Christof Monz
Christof Monz University of Amsterdam
Kevin Knight
Kevin Knight University of Southern California
Miles Osborne
Miles Osborne Bloomberg LP
Lucia Specia
Lucia Specia Imperial College London
Kevin Duh
Kevin Duh Johns Hopkins University
Rico Sennrich
Rico Sennrich University of Zurich
Daniel Marcu
Daniel Marcu University of Southern California
Jason Eisner
Jason Eisner Johns Hopkins University

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