NLPExplorer

Christian Federmann

Number of Papers:- 70

Number of Citations:- 208

First ACL Paper:- 2007

Latest ACL Paper:- 2024

Venues:-

EMNLP

AMTA

WMT

COLING

EACL

ACL

MTSummit

Findings

EAMT

NLP-COVID19

IWSLT

SSST

HumEval

LREC

Co-Authors:-

Similar Authors:-

Navigating the Metrics Maze: Reconciling Score Magnitudes and Accuracies ACL

Tom Kocmi | Vilém Zouhar | Christian Federmann | Matt Post |

Findings of the WMT 2024 Shared Task of the Open Language Data Initiative WMT

Findings of the WMT24 General Machine Translation Shared Task: The LLM Era Is Here but MT Is Not Solved Yet WMT

Findings of the 2023 Conference on Machine Translation (WMT23): LLMs Are Here but Not Quite There Yet WMT

GEMBA-MQM: Detecting Translation Quality Error Spans with GPT-4 WMT

Tom Kocmi | Christian Federmann |

evision PDF of 'Findings of the IWSLT 2022 Evaluation Campaign ACL IWSLT

Findings of the WMT’22 Shared Task on Large-Scale Machine Translation Evaluation for African Languages WMT

MS-COMET: More and Better Human Judgements Improve Metric Performance WMT

Tom Kocmi | Hitokazu Matsushita | Christian Federmann |

Findings of the 2022 Conference on Machine Translation (WMT22) WMT

Searching for a Higher Power in the Human Evaluation of MT WMT

Johnny Wei | Tom Kocmi | Christian Federmann |

Proceedings of the Seventh Conference on Machine Translation (WMT) WMT

On User Interfaces for Large-Scale Document-Level Human Evaluation of Machine Translation Outputs EACL HumEval

Roman Grundkiewicz | Marcin Junczys-Dowmunt | Christian Federmann | Tom Kocmi |

To Ship or Not to Ship: An Extensive Evaluation of Automatic Metrics for Machine Translation EMNLP WMT

Proceedings of the Sixth Conference on Machine Translation EMNLP WMT

The JHU-Microsoft Submission for WMT21 Quality Estimation Shared Task EMNLP WMT

Findings of the 2021 Conference on Machine Translation (WMT21) EMNLP WMT

FINDINGS OF THE IWSLT 2020 EVALUATION CAMPAIGN ACL IWSLT WS

Findings of the 2020 Conference on Machine Translation (WMT20) EMNLP WMT

Assessing Human-Parity in Machine Translation on the Segment Level EMNLP Findings

Yvette Graham | Christian Federmann | Maria Eskevich | Barry Haddow |

TICO-19: the Translation Initiative for COvid-19 EMNLP NLP-COVID19

Proceedings of the Fifth Conference on Machine Translation EMNLP WMT

Proceedings of the 14th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Track) AMTA

Michael Denkowski | Christian Federmann |

Multilingual Whispers: Generating Paraphrases with Translation EMNLP WS

Christian Federmann | Oussama Elachqar | Chris Quirk |

Proceedings of the Fourth Conference on Machine Translation (Volume 1: Research Papers) ACL WMT WS

Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1) ACL WMT WS

Findings of the 2019 Conference on Machine Translation (WMT19) ACL WMT WS

Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2) ACL WMT WS

evision PDF of 'Findings of the WMT 2019 Shared Tasks on Quality Estimation ACL WMT WS

Findings of the WMT 2019 Shared Task on Automatic Post-Editing ACL WMT WS

Rajen Chatterjee | Christian Federmann | Matteo Negri | Marco Turchi |

Domain Adaptation of Document-Level NMT in IWSLT19 EMNLP IWSLT

Martin Popel | Christian Federmann |

Appraise Evaluation Framework for Machine Translation COLING

Christian Federmann |

Proceedings of the Third Conference on Machine Translation: Research Papers EMNLP WMT WS

Findings of the 2018 Conference on Machine Translation (WMT18) EMNLP WMT WS

Machine Translation Human Evaluation: an investigation of evaluation based on Post-Editing and its relation with Direct Assessment EMNLP IWSLT

Luisa Bentivogli | Mauro Cettolo | Marcello Federico | Christian Federmann |

Proceedings of the Second Conference on Machine Translation WMT WS

Findings of the 2017 Conference on Machine Translation (WMT17) WMT WS

Overview of the IWSLT 2017 Evaluation Campaign IWSLT

The Microsoft Speech Language Translation (MSLT) Corpus for Chinese and Japanese: Conversational Test data for Machine Translation and Speech Recognition MTSummit

Christian Federmann | William D. Lewis |

Proceedings of the First Conference on Machine Translation: Volume 1, Research Papers WMT WS

Findings of the 2016 Conference on Machine Translation WMT WS

Microsoft Speech Language Translation (MSLT) Corpus: The IWSLT 2016 release for English, French and German IWSLT

Christian Federmann | William D. Lewis |

Proceedings of the Tenth Workshop on Statistical Machine Translation WMT WS

Findings of the 2015 Workshop on Statistical Machine Translation WMT WS

Applying cross-entropy difference for selecting parallel training data from publicly available sources for conversational machine translation IWSLT

William Lewis | Christian Federmann | Ying Xin |

Proceedings of the Ninth Workshop on Statistical Machine Translation WMT WS

Findings of the 2014 Workshop on Statistical Machine Translation WMT WS

Findings of the 2013 Workshop on Statistical Machine Translation WMT WS

Experiments with Term Translation COLING

Mihael Arcan | Christian Federmann | Paul Buitelaar |

Involving Language Professionals in the Evaluation of Machine Translation LREC

A Richly Annotated, Multilingual Parallel Corpus for Hybrid Machine Translation LREC

META-SHARE v2: An Open Network of Repositories for Language Resources including Data and Tools LREC

The ML4HMT Workshop on Optimising the Division of Labour in Hybrid Machine Translation LREC

Can Machine Learning Algorithms Improve Phrase Selection in Hybrid Machine Translation? WS

Christian Federmann |

Machine Learning for Hybrid Machine Translation WMT WS

Sabine Hunsicker | Yu Chen | Christian Federmann |

Using Domain-specific and Collaborative Resources for Term Translation SSST WS

Mihael Arcan | Christian Federmann | Paul Buitelaar |

Proceedings of the Second Workshop on Applying Machine Learning Techniques to Optimise the Division of Labour in Hybrid MT WS

System Combination Using Joint, Binarised Feature Vectors WS

Christian Federmann |

Results from the ML4HMT-12 Shared Task on Applying Machine Learning Techniques to Optimise the Division of Labour in Hybrid Machine Translation WS