---
title: "Wolfgang Macherey — papers and cards"
description: "Wolfgang Macherey: 2 paper cards in the Research library (2020–2021), with what each paper is about, the ideas Mova took from it, and the co-authors."
canonical: "https://research.elamur.ai/free/en/authors/wolfgang-macherey/"
---
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# Wolfgang Macherey

2 paper cards in the Research library · 2020–2021

Wolfgang Macherey wrote 2 of the papers Mova reads, in 2020–2021, most of them on [Machine translation](https://md.research.elamur.ai/free/en/topics/machine-translation/); often with [Markus Freitag](https://md.research.elamur.ai/free/en/authors/markus-freitag/), David Grangier, Genady Beryozkin.

[OpenAlex](https://openalex.org/A5018646392) · [**h-index 27**](https://openalex.org/authors/A5018646392) · [8785 citations](https://openalex.org/authors/A5018646392) · [58 works](https://openalex.org/works?filter=author.id:A5018646392) — openalex-snapshot, 2026-10-14

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Wolfgang+Macherey) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Wolfgang+Macherey) · [dblp](https://dblp.org/search?q=Wolfgang+Macherey) · [ACL Anthology](https://aclanthology.org/search/?q=Wolfgang+Macherey) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Wolfgang+Macherey)

Topics: [Machine translation](https://md.research.elamur.ai/free/en/topics/machine-translation/) 2

## Papers

1. **[Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation](https://md.research.elamur.ai/free/en/papers/freitag-2021-experts-errors-context-large-scale/)** *(2021)* The paper replaces the usual one-score human judgment with explicit error annotation. Professional translators, working with the full document, marked errors in the outputs of the ten top systems of WMT 2020 (human references included) for English-to-German and Chinese-to-English, using the MQM framework. The errors…
2. **[KoBE: Knowledge-Based Machine Translation Evaluation](https://md.research.elamur.ai/free/en/papers/gekhman-2020-kobe-knowledge-based-machine-translation/)** *(2020)* KoBE is a reference-free metric. Each source sentence and each candidate translation is linked to a large multilingual knowledge base, using entity linking. The score is the recall of source entities that are linked to the same knowledge-base entry in the candidate, clipped by the number of times each entity occurs…

## Co-authors (8)

- [Markus Freitag](https://md.research.elamur.ai/free/en/authors/markus-freitag/) ×2
- David Grangier
- Genady Beryozkin
- [George Foster](https://md.research.elamur.ai/free/en/authors/george-foster/)
- Qijun Tan
- [Roee Aharoni](https://md.research.elamur.ai/free/en/authors/roee-aharoni/)
- Viresh Ratnakar
- Zorik Gekhman

## More papers in the library (4)

Pages of the Research library: our summary, the ideas, references and who cites each.

- [Reinforced Self-Training (ReST) for Language Modeling](https://md.research.elamur.ai/free/en/papers/gulcehre-2023-reinforced-self-training-rest-language/) — Caglar Gulcehre, Tom Le Paine, Srivatsan Srinivasan, et al. · 2023
- [Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges](https://md.research.elamur.ai/free/en/papers/arivazhagan-2019-massively-multilingual-neural-machine-translation/) — Naveen Arivazhagan, Ankur Bapna, Orhan Firat, et al. · 2019
- [The Best of Both Worlds: Combining Recent Advances in Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/chen-2018-best-both-worlds-combining-recent/) — Mia Xu Chen, Orhan Firat, Ankur Bapna, et al. · 2018
- [Lattice-based Minimum Error Rate Training for Statistical Machine Translation](https://md.research.elamur.ai/free/en/papers/macherey-2008-lattice-based-minimum-error-rate/) — Wolfgang Macherey, Franz Och, Ignacio Thayer, et al. · 2008
