---
title: "Germany — research institutions, scientists and papers"
description: "Germany: 69 institutions with papers in our library in 26 agglomerations, 263 people with a page, 552 works, 613,223 citations."
canonical: "https://research.elamur.ai/free/en/countries/germany/"
---
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# Germany

Country 69 institutions in 26 agglomerations · [all countries](https://md.research.elamur.ai/free/en/countries/)

[**69** institutions with a page](https://md.research.elamur.ai/free/en/countries/germany/#institutions) · [**26** agglomerations](https://md.research.elamur.ai/free/en/countries/germany/#agglomerations) · [**263** people with a page](https://md.research.elamur.ai/free/en/countries/germany/#authors) · [**552** works in our library](https://md.research.elamur.ai/free/en/countries/germany/#works) · [**613,223** citations of their works](https://md.research.elamur.ai/free/en/countries/germany/#works)

## About

### Profile

Germany appears on this site as a country with a dense network of research organisations whose scientists wrote papers held in the library. Most of them are universities. There are also research institutes, a few company research groups and one university hospital, spread across many of the country's research cities. The order of institutions follows the cited work their scientists did there, so a few highly cited papers can count for as much as a long run of modestly cited ones. Read this way, the German entry describes where German contributions to this collection come from. It is not a survey of German science.

The research gathered here is overwhelmingly in [natural language processing](https://md.research.elamur.ai/free/en/shelves/nlp/) and its neighbours: [machine translation](https://md.research.elamur.ai/free/en/topics/machine-translation/), parsing and treebanks, discourse and anaphora, sentiment and offensive language, evaluation, and more recently [language models](https://md.research.elamur.ai/free/en/topics/language-models/). Around that core sit a few works from scientific computing, computer vision and education, which are among the most cited German works on the site. The institutions with the largest bodies of work are [Saarland University](https://md.research.elamur.ai/free/en/universities/saarland-university/), the [University of Stuttgart](https://md.research.elamur.ai/free/en/universities/university-of-stuttgart/) and [Technische Universität Darmstadt](https://md.research.elamur.ai/free/en/universities/technische-universitat-darmstadt/). The most cited bodies of work belong to the universities of [Munich](https://md.research.elamur.ai/free/en/agglomerations/munich/), where [Ludwig-Maximilians-Universität München](https://md.research.elamur.ai/free/en/universities/ludwig-maximilians-universitat-munchen/) and the [Technical University of Munich](https://md.research.elamur.ai/free/en/universities/technical-university-of-munich/) both stand out, and to [Constructor University](https://md.research.elamur.ai/free/en/universities/constructor-university/) in Bremen.

### History

Among the works here, German research begins with linguistic theory rather than engineering. The earliest piece is a 1989 study from Universität Hamburg on plural anaphora, which asks how a pronoun like "they" can refer back to a group that the earlier text never named as one. A 1993 paper on text-translation alignment, connected to the Technical University of Munich, looks at matching sentences and words between a text and its translation.

The late 1990s and early 2000s bring statistical methods. Thorsten Joachims's 1998 study of support vector machines for text categorization belongs to TU Dortmund University. In 2000 two statistical works appeared: TnT, Thorsten Brants's part-of-speech tagger from Saarland University, and the alignment models of Franz Josef Och and Hermann Ney from [RWTH Aachen University](https://md.research.elamur.ai/free/en/universities/rwth-aachen-university/). Grammar engineering appears in 2002 with the Parallel Grammar Project, connected to Stuttgart.

From the late 2000s the collection broadens into resources, shared tasks and toolkits: coreference systems such as BART, the CoNLL-2009 shared task on syntactic and semantic dependencies, fast dependency parsers from Stuttgart, annotation studies of information structure, and lexicon-based sentiment analysis. The years 2014 and 2015 mark a break, with neural sequence-to-sequence translation and attention models linked to Constructor University. After that the German collection grows quickly. Evaluation metrics, adapters and multilingual transfer, few-shot learning with language models, benchmarks for low-resource languages, and work on large language models in education and medicine follow. The most recent work here, from 2025, is a broad benchmark for frontier models.

### Research profile

Machine translation is the most visible strand. It runs from Och and Ney's statistical alignment models through the neural translation papers of 2014 to evaluation work. Maja Popović's chrF metric of 2015, scoring translations by overlapping character sequences, was followed by a 2016 study of its parameters and by chrF++ in 2017, which adds word sequences. These works are tied to [Humboldt-Universität zu Berlin](https://md.research.elamur.ai/free/en/universities/humboldt-universitat-zu-berlin/). German institutions also appear among the authors of the yearly findings of the Conference on Machine Translation, such as [the 2016 overview](https://md.research.elamur.ai/free/en/papers/bojar-2016-findings-2016-conference-machine-translation/) and the 2019 edition. They also appear in a 2017 biomedical translation task and in the [Nematus](https://md.research.elamur.ai/free/en/papers/sennrich-2017-nematus-toolkit-neural-machine-translation/) toolkit for neural translation. Evaluation as a topic reaches beyond translation, for instance in MoverScore from Darmstadt, which compares generated and reference texts through contextual embeddings.

Syntax, parsing and morphology form a second strand, concentrated in Stuttgart, Saarbrücken and Tübingen. Bernd Bohnet's [fast dependency parser](https://md.research.elamur.ai/free/en/papers/bohnet-2010-top-accuracy-fast-dependency-parsing/) of 2010 showed that high-accuracy graph-based parsing need not be slow. A 2012 transition-based system predicts part-of-speech tags and labelled trees together. Helmut Schmid's decision-tree estimation targets tagging with very large, detailed tagsets. Shared tasks give this strand its public face: the CoNLL-2009 task, the 2013 task on parsing morphologically rich languages, and the [CoNLL 2017 task](https://md.research.elamur.ai/free/en/papers/zeman-2017-conll-2017-shared-task-multilingual/) on parsing raw text into [Universal Dependencies](https://md.research.elamur.ai/free/en/topics/universal-dependencies/). UniMorph 3.0 extends the work to cross-lingual morphology.

Discourse, coreference and argumentation make a third strand, centred on Potsdam, Heidelberg, Tübingen and Hamburg. The BART toolkit for [coreference resolution](https://md.research.elamur.ai/free/en/topics/coreference-resolution/) and its multilingual extension, corpora annotated for anaphora in Italian and English, a study of bridging resolution, and a survey of anaphors with non-nominal antecedents all belong here. From the [University of Potsdam](https://md.research.elamur.ai/free/en/universities/university-of-potsdam/) come discourse parsing for argumentation mining, a lexicon of English discourse connectives and the Potsdam Commentary Corpus. Darmstadt contributes [argumentation parsing in persuasive essays](https://md.research.elamur.ai/free/en/papers/stab-2017-parsing-argumentation-structures-persuasive-essays/).

Sentiment, opinion and harmful language are a fourth strand. [Lexicon-based sentiment analysis](https://md.research.elamur.ai/free/en/papers/taboada-2011-lexicon-based-methods-sentiment-analysis/), connected to Potsdam, proposes a semantic orientation calculator in place of purely trained classifiers. Darmstadt worked on extracting opinion targets across domains. The Saarland survey on hate speech detection argues that keyword filters cannot capture context, and Tübingen built a Turkish corpus of offensive language on social media.

Representation learning and language models are the most recent strand. Darmstadt's multilingual sentence embeddings via knowledge distillation and its adapter work (AdapterFusion, MAD-X and AdapterHub) let one model serve many tasks and languages without full copies. Munich contributes pattern-exploiting training for few-shot learning, probes of what pretrained models know, and a convolutional attention network for sentence pairs. [Low-resource languages](https://md.research.elamur.ai/free/en/topics/low-resource-languages/), especially African languages, form a distinct cluster through named entity recognition, participatory translation research and audits of web-crawled multilingual corpora. Other lines include readability classification inspired by second language acquisition, incremental [dialogue systems](https://md.research.elamur.ai/free/en/topics/dialogue-systems/), and unsupervised detection of lexical semantic change in a 2020 SemEval task.

### Leading scientists

[Dzmitry Bahdanau](https://md.research.elamur.ai/free/en/authors/dzmitry-bahdanau/), at Constructor University, is the author of the attention-based neural translation model of 2014. Bahdanau also co-wrote the study of encoder–decoder translation and the 2015 work carrying attention into speech recognition.

[Olaf Ronneberger](https://md.research.elamur.ai/free/en/authors/olaf-ronneberger/) is connected to the University of Freiburg and has a small but heavily cited set of papers in our library.

[Franz Josef Och](https://md.research.elamur.ai/free/en/authors/franz-josef-och/), at RWTH Aachen University, is known here for statistical alignment models that link words across parallel texts, written with [Hermann Ney](https://md.research.elamur.ai/free/en/authors/hermann-ney/). Ney's body of work at Aachen centres on the same statistical approach to translation.

[Iryna Gurevych](https://md.research.elamur.ai/free/en/authors/iryna-gurevych/) of Technische Universität Darmstadt has the largest set of papers among the people shown first. The work spans argumentation mining, sound reporting of experimental results, multilingual sentence embeddings and adapter-based transfer learning.

[Thorsten Joachims](https://md.research.elamur.ai/free/en/authors/thorsten-joachims/), at TU Dortmund University, showed in 1998 why support vector machines fit text categorization, where documents have many relevant features.

[Hinrich Schütze](https://md.research.elamur.ai/free/en/authors/hinrich-schutze/) of Ludwig-Maximilians-Universität München co-wrote the pattern-exploiting training papers and ABCNN. Schütze is one of the main figures behind Munich's work on language models.

[Christian Federmann](https://md.research.elamur.ai/free/en/authors/christian-federmann/) is attached to the [German Research Centre for Artificial Intelligence](https://md.research.elamur.ai/free/en/labs/german-research-centre-for-artificial-intelligence/) and appears among the organisers and authors of the WMT findings.

[Timo Schick](https://md.research.elamur.ai/free/en/authors/timo-schick/), also in Munich, is the first author of both few-shot papers. These recast classification tasks as cloze questions and showed that small language models can learn from few examples.

[Marcos Zampieri](https://md.research.elamur.ai/free/en/authors/marcos-zampieri/) at Saarland University, [Daryna Dementieva](https://md.research.elamur.ai/free/en/authors/daryna-dementieva/) at the Technical University of Munich, and [Ivan Vulić](https://md.research.elamur.ai/free/en/authors/ivan-vulic/) at the [University of Mannheim](https://md.research.elamur.ai/free/en/universities/university-of-mannheim/) complete the first group. Their work is cited mainly in language technology and multilingual processing.

### Landmark works

The most cited German work on the site is [SciPy 1.0](https://md.research.elamur.ai/free/en/papers/virtanen-2019-scipy-1-0-fundamental-algorithms/), the paper describing the open-source Python library for scientific computing. Many German institutions are among its affiliations, including both Munich universities, Stuttgart, Heidelberg, Tübingen and Humboldt-Universität zu Berlin.

Next comes [Neural Machine Translation by Jointly Learning to Align and Translate](https://md.research.elamur.ai/free/en/papers/bahdanau-2014-neural-machine-translation-jointly-learning/). It introduced RNNsearch, letting the decoder attend to different parts of the source sentence instead of squeezing it into one fixed vector. Its companion, [On the Properties of Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/cho-2014-properties-neural-machine-translation-encoder/), examined when early encoder–decoder systems succeed and fail, particularly on long sentences.

[Text Categorization with Support Vector Machines](https://md.research.elamur.ai/free/en/papers/joachims-1998-text-categorization-support-vector-machines/) is the oldest of the most cited works. [ChatGPT for Good?](https://md.research.elamur.ai/free/en/papers/kasneci-2023-chatgpt-good-opportunities-challenges-large/), linked to both Munich universities, is a position paper on the chances and risks of large language models in education. It presents no new model or benchmark. [Visual Genome](https://md.research.elamur.ai/free/en/papers/krishna-2016-visual-genome-connecting-language-vision/) offers densely annotated images that tie objects, attributes and relations to language. [A Call for Clarity in Reporting BLEU Scores](https://md.research.elamur.ai/free/en/papers/post-2018-call-clarity-reporting-bleu-scores/) released SacreBLEU so that translation scores can be compared fairly.

Further down the most cited works come a review of continual lifelong learning in neural networks from Hamburg, a systematic study of topic coherence measures, [chrF](https://md.research.elamur.ai/free/en/papers/popovic-2015-chrf-character-n-gram-f/), a long tutorial survey of knowledge graphs, the hate speech survey, and [Exploiting Cloze-Questions](https://md.research.elamur.ai/free/en/papers/schick-2021-exploiting-cloze-questions-few-shot/). [TnT](https://md.research.elamur.ai/free/en/papers/brants-2000-tnt-statistical-part-speech-tagger/) belongs to the same tier; it showed that a carefully engineered second-order hidden Markov tagger can match more complex methods.

### Labs and units

The German entry gathers universities, research institutes, companies and a hospital. Among universities, Saarland University and the University of Stuttgart have the largest bodies of work. Darmstadt and the two Munich universities follow, together with [Heidelberg University](https://md.research.elamur.ai/free/en/universities/heidelberg-university/), the [University of Tübingen](https://md.research.elamur.ai/free/en/universities/university-of-tubingen/), Universität Hamburg, the University of Potsdam, [Leipzig University](https://md.research.elamur.ai/free/en/universities/leipzig-university/), TU Dortmund University and RWTH Aachen University.

Non-university institutes form the second group. The German Research Centre for Artificial Intelligence in Kaiserslautern has one of the larger German sets of papers. The [Heidelberg Institute for Theoretical Studies](https://md.research.elamur.ai/free/en/labs/heidelberg-institute-for-theoretical-studies/) has a substantial body of work with more modest citation. The [Max Planck Society](https://md.research.elamur.ai/free/en/labs/max-planck-society/) has a small, heavily cited set. Several of its institutes appear separately, including the [Max Planck Institute for Informatics](https://md.research.elamur.ai/free/en/labs/max-planck-institute-for-informatics/) and the [Max Planck Institute for Software Systems](https://md.research.elamur.ai/free/en/labs/max-planck-institute-for-software-systems/), both in Saarbrücken. The DIPF institute in Frankfurt am Main adds education research.

Industry appears through [Amazon (Germany)](https://md.research.elamur.ai/free/en/companies/amazon-germany/) in Berlin, Microsoft's German office in Munich, [Robert Bosch](https://md.research.elamur.ai/free/en/companies/robert-bosch-germany/) in Stuttgart, Bayer in Leverkusen and the [European Media Laboratory](https://md.research.elamur.ai/free/en/companies/european-media-laboratory/) in Heidelberg. [Charité – Universitätsmedizin Berlin](https://md.research.elamur.ai/free/en/hospitals/charite-universitatsmedizin-berlin/) is the single hospital.

### Collaborations

Many German works are joint products of several institutions in the country. The SciPy paper and Humanity's Last Exam each draw in many German universities and institutes. Shared-task overviews, such as the WMT findings and the CoNLL tasks, connect Saarbrücken, Munich, Stuttgart, Tübingen and Berlin with partners abroad.

Some people link institutions directly. Sebastian Padó and Stefan Riezler appear in both Stuttgart and Heidelberg. Yannick Versley connects Heidelberg and Tübingen through the BART coreference toolkit. Chris Biemann links Darmstadt and Hamburg, Jonas Pfeiffer links Darmstadt and the Technical University of Munich, and Helmut Schmid links Stuttgart and Munich. Within a few works the same partners recur: the ARRAU anaphora paper joins Hamburg and Potsdam, the information-structure annotation study joins Potsdam and Humboldt-Universität zu Berlin, and the 2017 biomedical translation task also joins Potsdam and Berlin.

The African-language works form a cross-institutional cluster that includes Constructor University, the Technical University of Munich, Universität Hamburg and Saarland University. In that cluster, MasakhaNER, participatory translation research and an audit of web-crawled corpora come out of broad community efforts. Links between industry and academia show mainly in the cities where companies sit beside universities: Berlin, Munich, Stuttgart and Heidelberg.

### Timeline

From 1989 to the late 1990s, the few works here are linguistic and theoretical: plural anaphora in Hamburg, translation alignment in Munich, and Joachims's text categorization study of 1998 in Dortmund.

From 2000 to 2009, statistical language processing takes hold. TnT and the Aachen alignment models open the decade. The Parallel Grammar Project follows in 2002 and the ELAN annotation framework in 2006. Semantic roles for question answering appear in 2007, and the BART toolkit, decision-tree tagging and information-structure annotation in 2008. The CoNLL-2009 shared task closes the period.

From 2010 to 2013, parsing and resources dominate. Fast and joint dependency parsing come from Stuttgart, multilingual coreference and opinion-target extraction from other groups. Lexicon-based sentiment analysis and incremental dialogue processing appear in 2011, readability classification and cross-domain temporal tagging in 2012. The SPMRL shared task of 2013 ends the period.

From 2014 to 2018, neural methods arrive with attention-based translation and speech recognition. Evaluation work follows with chrF, the BLEU reporting paper and score distributions. Argumentation parsing, the hate speech survey, Nematus, the CoNLL 2017 task, Visual Genome and the continual learning review also fall in these years.

From 2019 to 2025, work centres on pretrained models and broad resources. This period brings SciPy 1.0, MoverScore, adapters and multilingual embeddings, few-shot pattern-exploiting training, probes of language models, and benchmarks for legal language and semantic change. It also includes efforts for African languages, LAION-400M and the ROOTS corpus, and studies of large language models in education and medicine. It ends with Humanity's Last Exam in 2025.

## Where

## Agglomerations (26)

1. [**Frankfurt am Main**5 institutions*18,715 citations*](https://md.research.elamur.ai/free/en/agglomerations/frankfurt/)
2. [**Saarbruecken**4 institutions*58,971 citations*](https://md.research.elamur.ai/free/en/agglomerations/saarbruecken/)
3. [**Munich**6 institutions*184,254 citations*](https://md.research.elamur.ai/free/en/agglomerations/munich/)
4. [**Stuttgart**5 institutions*89,050 citations*](https://md.research.elamur.ai/free/en/agglomerations/stuttgart/)
5. [**Berlin**9 institutions*53,998 citations*](https://md.research.elamur.ai/free/en/agglomerations/berlin/)
6. [**Mannheim**4 institutions*45,641 citations*](https://md.research.elamur.ai/free/en/agglomerations/mannheim/)
7. [**Rhine-Ruhr**8 institutions*15,319 citations*](https://md.research.elamur.ai/free/en/agglomerations/essen/)
8. [**Heerlen**2 institutions*5,695 citations*](https://md.research.elamur.ai/free/en/agglomerations/aachen/)
9. [**Bremen**2 institutions*68,160 citations*](https://md.research.elamur.ai/free/en/agglomerations/bremen/)
10. [**Kaiserslautern**1 institution*5,199 citations*](https://md.research.elamur.ai/free/en/agglomerations/kaiserslautern/)
11. [**Leipzig**2 institutions*7,306 citations*](https://md.research.elamur.ai/free/en/agglomerations/leipzig/)
12. [**Hamburg**1 institution*4,538 citations*](https://md.research.elamur.ai/free/en/agglomerations/hamburg/)
13. [**Dresden**2 institutions*7,148 citations*](https://md.research.elamur.ai/free/en/agglomerations/dresden/)
14. [**Freiburg im Breisgau**1 institution*851 citations*](https://md.research.elamur.ai/free/en/agglomerations/freiburg-im-breisgau/)
15. [**Bielefeld**1 institution*574 citations*](https://md.research.elamur.ai/free/en/agglomerations/bielefeld/)
16. [**Paderborn**1 institution*3,209 citations*](https://md.research.elamur.ai/free/en/agglomerations/paderborn/)
17. [**Karlsruhe**1 institution*425 citations*](https://md.research.elamur.ai/free/en/agglomerations/karlsruhe/)
18. [**Osnabrück**1 institution*205 citations*](https://md.research.elamur.ai/free/en/agglomerations/osnabruck/)
19. [**Kiel**1 institution*38,850 citations*](https://md.research.elamur.ai/free/en/agglomerations/kiel/)
20. [**Constance**1 institution*118 citations*](https://md.research.elamur.ai/free/en/agglomerations/constance/)
21. [**Göttingen**1 institution*146 citations*](https://md.research.elamur.ai/free/en/agglomerations/gottingen/)
22. [**Jena**1 institution*187 citations*](https://md.research.elamur.ai/free/en/agglomerations/jena/)
23. [**Münster**1 institution*448 citations*](https://md.research.elamur.ai/free/en/agglomerations/munster/)
24. [**Magdeburg**1 institution*114 citations*](https://md.research.elamur.ai/free/en/agglomerations/magdeburg/)
25. [**Hanover**2 institutions*584 citations*](https://md.research.elamur.ai/free/en/agglomerations/hanover/)

[See all 26 agglomerations →](https://md.research.elamur.ai/free/en/countries/germany/agglomerations/)

## Institutions (69)

### 🎓 Universities (48)

1. **[Technische Universität Darmstadt](https://md.research.elamur.ai/free/en/universities/technische-universitat-darmstadt/)**University · [Darmstadt](https://md.research.elamur.ai/free/en/agglomerations/frankfurt/), Germany*58 works · 15,788 citations*
2. **[Saarland University](https://md.research.elamur.ai/free/en/universities/saarland-university/)**University · [Saarbrücken](https://md.research.elamur.ai/free/en/agglomerations/saarbruecken/), Germany*86 works · 15,761 citations*
3. **[University of Stuttgart](https://md.research.elamur.ai/free/en/universities/university-of-stuttgart/)**University · [Stuttgart](https://md.research.elamur.ai/free/en/agglomerations/stuttgart/), Germany*64 works · 45,339 citations*
4. **[Ludwig-Maximilians-Universität München](https://md.research.elamur.ai/free/en/universities/ludwig-maximilians-universitat-munchen/)**University · [Munich](https://md.research.elamur.ai/free/en/agglomerations/munich/), Germany*34 works · 53,994 citations*
5. **[RWTH Aachen University](https://md.research.elamur.ai/free/en/universities/rwth-aachen-university/)**University · [Aachen](https://md.research.elamur.ai/free/en/agglomerations/aachen/), Germany*15 works · 4,501 citations*
6. **[TU Dortmund University](https://md.research.elamur.ai/free/en/universities/tu-dortmund-university/)**University · [Dortmund](https://md.research.elamur.ai/free/en/agglomerations/essen/), Germany*5 works · 9,745 citations*
7. **[Constructor University](https://md.research.elamur.ai/free/en/universities/constructor-university/)**University · [Bremen](https://md.research.elamur.ai/free/en/agglomerations/bremen/), Germany*7 works · 29,782 citations*
8. **[University of Potsdam](https://md.research.elamur.ai/free/en/universities/university-of-potsdam/)**University · [Potsdam](https://md.research.elamur.ai/free/en/agglomerations/berlin/), Germany*31 works · 4,698 citations*
9. **[Humboldt-Universität zu Berlin](https://md.research.elamur.ai/free/en/universities/humboldt-universitat-zu-berlin/)**University · [Berlin](https://md.research.elamur.ai/free/en/agglomerations/berlin/), Germany*12 works · 41,836 citations*
10. **[Leipzig University](https://md.research.elamur.ai/free/en/universities/leipzig-university/)**University · [Leipzig](https://md.research.elamur.ai/free/en/agglomerations/leipzig/), Germany*12 works · 4,703 citations*
11. **[University of Tübingen](https://md.research.elamur.ai/free/en/universities/university-of-tubingen/)**University · [Tübingen](https://md.research.elamur.ai/free/en/agglomerations/stuttgart/), Germany*26 works · 40,312 citations*
12. **[Technical University of Munich](https://md.research.elamur.ai/free/en/universities/technical-university-of-munich/)**University · [Munich](https://md.research.elamur.ai/free/en/agglomerations/munich/), Germany*15 works · 48,366 citations*
13. **[Heidelberg University](https://md.research.elamur.ai/free/en/universities/heidelberg-university/)**University · [Heidelberg](https://md.research.elamur.ai/free/en/agglomerations/mannheim/), Germany*20 works · 40,006 citations*
14. **[University of Mannheim](https://md.research.elamur.ai/free/en/universities/university-of-mannheim/)**University · [Mannheim](https://md.research.elamur.ai/free/en/agglomerations/mannheim/), Germany*12 works · 2,957 citations*
15. **[Bauhaus-Universität Weimar](https://md.research.elamur.ai/free/en/universities/bauhaus-universitat-weimar/)**University · Weimar, Germany*7 works · 2,668 citations*
16. **[Ruhr University Bochum](https://md.research.elamur.ai/free/en/universities/ruhr-university-bochum/)**University · [Bochum](https://md.research.elamur.ai/free/en/agglomerations/essen/), Germany*19 works · 1,147 citations*
17. **[Universität Hamburg](https://md.research.elamur.ai/free/en/universities/universitat-hamburg/)**University · [Hamburg](https://md.research.elamur.ai/free/en/agglomerations/hamburg/), Germany*33 works · 4,538 citations*
18. **[Technische Universität Dresden](https://md.research.elamur.ai/free/en/universities/technische-universitat-dresden/)**University · [Dresden](https://md.research.elamur.ai/free/en/agglomerations/dresden/), Germany*6 works · 7,135 citations*
19. **[University of Freiburg](https://md.research.elamur.ai/free/en/universities/university-of-freiburg/)**University · [Freiburg im Breisgau](https://md.research.elamur.ai/free/en/agglomerations/freiburg-im-breisgau/), Germany*3 works · 851 citations*
20. **[Bielefeld University](https://md.research.elamur.ai/free/en/universities/bielefeld-university/)**University · [Bielefeld](https://md.research.elamur.ai/free/en/agglomerations/bielefeld/), Germany*12 works · 574 citations*
21. **[Technische Universität Berlin](https://md.research.elamur.ai/free/en/universities/technische-universitat-berlin/)**University · [Berlin](https://md.research.elamur.ai/free/en/agglomerations/berlin/), Germany*8 works · 914 citations*
22. **[Johannes Gutenberg University Mainz](https://md.research.elamur.ai/free/en/universities/johannes-gutenberg-university-mainz/)**University · [Mainz](https://md.research.elamur.ai/free/en/agglomerations/frankfurt/), Germany*3 works · 662 citations*
23. **[Freie Universität Berlin](https://md.research.elamur.ai/free/en/universities/freie-universitat-berlin/)**University · [Berlin](https://md.research.elamur.ai/free/en/agglomerations/berlin/), Germany*8 works · 273 citations*
24. **[Paderborn University](https://md.research.elamur.ai/free/en/universities/paderborn-university/)**University · [Paderborn](https://md.research.elamur.ai/free/en/agglomerations/paderborn/), Germany*6 works · 3,209 citations*
25. **[Martin Luther University Halle-Wittenberg](https://md.research.elamur.ai/free/en/universities/martin-luther-university-halle-wittenberg/)**University · [Halle](https://md.research.elamur.ai/free/en/agglomerations/leipzig/), Germany*2 works · 2,603 citations*

[See all 48 universities in Germany →](https://md.research.elamur.ai/free/en/countries/germany/institutions/universities/)

### 🔬 Labs and research institutes (15)

1. **[German Research Centre for Artificial Intelligence](https://md.research.elamur.ai/free/en/labs/german-research-centre-for-artificial-intelligence/)**Research institute · [Kaiserslautern](https://md.research.elamur.ai/free/en/agglomerations/kaiserslautern/), Germany*39 works · 5,199 citations*
2. **[Heidelberg Institute for Theoretical Studies](https://md.research.elamur.ai/free/en/labs/heidelberg-institute-for-theoretical-studies/)**Research institute · [Heidelberg](https://md.research.elamur.ai/free/en/agglomerations/mannheim/), Germany*26 works · 1,828 citations*
3. **[Max Planck Institute for Informatics](https://md.research.elamur.ai/free/en/labs/max-planck-institute-for-informatics/)**Research institute · [Saarbrücken](https://md.research.elamur.ai/free/en/agglomerations/saarbruecken/), Germany*9 works · 3,657 citations*
4. **[Max Planck Society](https://md.research.elamur.ai/free/en/labs/max-planck-society/)**Research institute · [Munich](https://md.research.elamur.ai/free/en/agglomerations/munich/), Germany*7 works · 41,401 citations*
5. **[DIPF | Leibniz Institute for Research and Information in Education](https://md.research.elamur.ai/free/en/labs/dipf-leibniz-institute-for-research-and-information-in-education/)**Research institute · [Frankfurt am Main](https://md.research.elamur.ai/free/en/agglomerations/frankfurt/), Germany*6 works · 1,833 citations*
6. **[Helmholtz Center for Information Security](https://md.research.elamur.ai/free/en/labs/helmholtz-center-for-information-security/)**Research institute · [Saarbrücken](https://md.research.elamur.ai/free/en/agglomerations/saarbruecken/), Germany*4 works · 1,001 citations*
7. **[Forschungszentrum Jülich](https://md.research.elamur.ai/free/en/labs/forschungszentrum-julich/)**Research institute · [Jülich](https://md.research.elamur.ai/free/en/agglomerations/aachen/), Germany*3 works · 1,194 citations*
8. **[Fraunhofer Institute for Intelligent Analysis and Information Systems](https://md.research.elamur.ai/free/en/labs/fraunhofer-institute-for-intelligent-analysis-and-information-systems/)**Research institute · [Sankt Augustin](https://md.research.elamur.ai/free/en/agglomerations/essen/), Germany*3 works · 270 citations*
9. **[Hasso Plattner Institute](https://md.research.elamur.ai/free/en/labs/hasso-plattner-institute/)**Research institute · [Potsdam](https://md.research.elamur.ai/free/en/agglomerations/berlin/), Germany*4 works · 1,050 citations*
10. **[Hessian Center for Artificial Intelligence](https://md.research.elamur.ai/free/en/labs/hessian-center-for-artificial-intelligence/)**Research institute · [Darmstadt](https://md.research.elamur.ai/free/en/agglomerations/frankfurt/), Germany*2 works · 140 citations*
11. **[Max Planck Institute for Intelligent Systems](https://md.research.elamur.ai/free/en/labs/max-planck-institute-for-intelligent-systems/)**Research institute · [Stuttgart](https://md.research.elamur.ai/free/en/agglomerations/stuttgart/), Germany*2 works · 791 citations*
12. **[Institut für Mikroelektronik Stuttgart](https://md.research.elamur.ai/free/en/labs/institut-fur-mikroelektronik-stuttgart/)**Research institute · [Stuttgart](https://md.research.elamur.ai/free/en/agglomerations/stuttgart/), Germany*3 works · 396 citations*
13. **[Leibniz-Centre General Linguistics](https://md.research.elamur.ai/free/en/labs/leibniz-centre-general-linguistics/)**Research institute · [Berlin](https://md.research.elamur.ai/free/en/agglomerations/berlin/), Germany*3 works · 27 citations*
14. **[Max Planck Institute for Software Systems](https://md.research.elamur.ai/free/en/labs/max-planck-institute-for-software-systems/)**Research institute · [Saarbrücken](https://md.research.elamur.ai/free/en/agglomerations/saarbruecken/), Germany*2 works · 38,552 citations*
15. **[Max Planck Institute for Security and Privacy](https://md.research.elamur.ai/free/en/labs/max-planck-institute-for-security-and-privacy/)**Research institute · [Bochum](https://md.research.elamur.ai/free/en/agglomerations/essen/), Germany*2 works · 476 citations*

### 🏢 Companies (5)

1. **[Amazon (Germany)](https://md.research.elamur.ai/free/en/companies/amazon-germany/)**Company · [Berlin](https://md.research.elamur.ai/free/en/agglomerations/berlin/), Germany*3 works · 4,690 citations*
2. **[European Media Laboratory](https://md.research.elamur.ai/free/en/companies/european-media-laboratory/)**Company · [Heidelberg](https://md.research.elamur.ai/free/en/agglomerations/mannheim/), Germany*6 works · 850 citations*
3. **[Robert Bosch](https://md.research.elamur.ai/free/en/companies/robert-bosch-germany/)**Company · [Stuttgart](https://md.research.elamur.ai/free/en/agglomerations/stuttgart/), Germany*6 works · 2,212 citations*
4. **[Microsoft (Germany)](https://md.research.elamur.ai/free/en/companies/microsoft-germany/)**Company · [Munich](https://md.research.elamur.ai/free/en/agglomerations/munich/), Germany*3 works · 1,609 citations*
5. **[Bayer](https://md.research.elamur.ai/free/en/companies/bayer/)**Company · [Leverkusen](https://md.research.elamur.ai/free/en/agglomerations/essen/), Germany*2 works · 387 citations*

### 🏥 Hospitals and medical centres (1)

1. **[Charité – Universitätsmedizin Berlin](https://md.research.elamur.ai/free/en/hospitals/charite-universitatsmedizin-berlin/)**Hospital · [Berlin](https://md.research.elamur.ai/free/en/agglomerations/berlin/), Germany*3 works · 289 citations*

[See all 69 institutions in Germany →](https://md.research.elamur.ai/free/en/countries/germany/institutions/)

## People (263)

Authors with a page confirmed at its institutions, the most cited first.

1. [**Dzmitry Bahdanau**Constructor University*6 papers here · 56,164 citations*](https://md.research.elamur.ai/free/en/authors/dzmitry-bahdanau/)
2. [**Olaf Ronneberger**University of Freiburg*2 papers here · 46,711 citations*](https://md.research.elamur.ai/free/en/authors/olaf-ronneberger/)
3. [**Franz Josef Och**RWTH Aachen University*11 papers here · 23,468 citations*](https://md.research.elamur.ai/free/en/authors/franz-josef-och/)
4. [**Iryna Gurevych**Technische Universität Darmstadt*45 papers here · 16,946 citations*](https://md.research.elamur.ai/free/en/authors/iryna-gurevych/)
5. [**Hermann Ney**RWTH Aachen University*13 papers here · 13,687 citations*](https://md.research.elamur.ai/free/en/authors/hermann-ney/)
6. [**Thorsten Joachims**TU Dortmund University*2 papers here · 11,736 citations*](https://md.research.elamur.ai/free/en/authors/thorsten-joachims/)
7. [**Hinrich Schütze**Ludwig-Maximilians-Universität München*16 papers here · 11,134 citations*](https://md.research.elamur.ai/free/en/authors/hinrich-schutze/)
8. [**Christian Federmann**German Research Centre for Artificial Intelligence*17 papers here · 8,839 citations*](https://md.research.elamur.ai/free/en/authors/christian-federmann/)
9. [**Timo Schick**Ludwig-Maximilians-Universität München*9 papers here · 8,683 citations*](https://md.research.elamur.ai/free/en/authors/timo-schick/)
10. [**Marcos Zampieri**Saarland University*15 papers here · 7,896 citations*](https://md.research.elamur.ai/free/en/authors/marcos-zampieri/)
11. [**Daryna Dementieva**Technical University of Munich*4 papers here · 7,750 citations*](https://md.research.elamur.ai/free/en/authors/daryna-dementieva/)
12. [**Ivan Vulić**University of Mannheim*14 papers here · 7,366 citations*](https://md.research.elamur.ai/free/en/authors/ivan-vulic/)
13. [**Oliver Groth**Technische Universität Dresden*2 papers here · 6,662 citations*](https://md.research.elamur.ai/free/en/authors/oliver-groth/)
14. [**Nora Kassner**Ludwig-Maximilians-Universität München*3 papers here · 6,152 citations*](https://md.research.elamur.ai/free/en/authors/nora-kassner/)
15. [**Sebastian Krause**German Research Centre for Artificial Intelligence*3 papers here · 5,572 citations*](https://md.research.elamur.ai/free/en/authors/sebastian-krause/)
16. [**Bernd Bohnet**University of Stuttgart*13 papers here · 4,972 citations*](https://md.research.elamur.ai/free/en/authors/bernd-bohnet/)
17. [**Gerard de Melo**University of Potsdam*4 papers here · 4,734 citations*](https://md.research.elamur.ai/free/en/authors/gerard-de-melo/)
18. [**Michael Strube**Heidelberg Institute for Theoretical Studies*35 papers here · 4,587 citations*](https://md.research.elamur.ai/free/en/authors/michael-strube/)
19. [**Manfred Stede**University of Potsdam*22 papers here · 4,585 citations*](https://md.research.elamur.ai/free/en/authors/manfred-stede/)
20. [**Nils Reimers**Technische Universität Darmstadt*11 papers here · 4,411 citations*](https://md.research.elamur.ai/free/en/authors/nils-reimers/)
21. [**Matthias Huck**Ludwig-Maximilians-Universität München*6 papers here · 4,366 citations*](https://md.research.elamur.ai/free/en/authors/matthias-huck/)
22. [**Benno Stein**Leipzig University*7 papers here · 4,317 citations*](https://md.research.elamur.ai/free/en/authors/benno-stein/)
23. [**Thorsten Brants**Saarland University*5 papers here · 4,254 citations*](https://md.research.elamur.ai/free/en/authors/thorsten-brants/)
24. [**Maja Popović**RWTH Aachen University*7 papers here · 4,207 citations*](https://md.research.elamur.ai/free/en/authors/maja-popovic/)
25. [**Martin Potthast**Leipzig University*5 papers here · 4,003 citations*](https://md.research.elamur.ai/free/en/authors/martin-potthast/)

[See all 263 people →](https://md.research.elamur.ai/free/en/countries/germany/people/)

## Works in our library (552)

Works of its institutions, the most cited first.

1. [**SciPy 1.0 — Fundamental Algorithms for Scientific Computing in Python**Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, et al.*2019 · 38,317 citations*](https://md.research.elamur.ai/free/en/papers/virtanen-2019-scipy-1-0-fundamental-algorithms/)
2. [**Neural Machine Translation by Jointly Learning to Align and Translate**Dzmitry Bahdanau, Kyunghyun Cho, Yoshua Bengio*2014 · 18,908 citations*](https://md.research.elamur.ai/free/en/papers/bahdanau-2014-neural-machine-translation-jointly-learning/)
3. [**Text Categorization with Support Vector Machines: Learning with Many Relevant Features**Thorsten Joachims*1998 · 8,304 citations*](https://md.research.elamur.ai/free/en/papers/joachims-1998-text-categorization-support-vector-machines/)
4. [**On the Properties of Neural Machine Translation: Encoder-Decoder Approaches**Kyunghyun Cho, Bart van Merrienboer, Dzmitry Bahdanau, et al.*2014 · 7,734 citations*](https://md.research.elamur.ai/free/en/papers/cho-2014-properties-neural-machine-translation-encoder/)
5. [**ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education**Enkelejda Kasneci, Kathrin Seßler, Stefan Küchemann, et al.*2023 · 7,429 citations*](https://md.research.elamur.ai/free/en/papers/kasneci-2023-chatgpt-good-opportunities-challenges-large/)
6. [**Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations**Ranjay Krishna, Yuke Zhu, Oliver Groth, et al.*2016 · 5,747 citations*](https://md.research.elamur.ai/free/en/papers/krishna-2016-visual-genome-connecting-language-vision/)
7. [**A Call for Clarity in Reporting BLEU Scores**Matt Post*2018 · 4,130 citations*](https://md.research.elamur.ai/free/en/papers/post-2018-call-clarity-reporting-bleu-scores/)
8. [**Lexicon-Based Methods for Sentiment Analysis**Maite Taboada, Julian Brooke, Milan Tofiloski, et al.*2011 · 3,556 citations*](https://md.research.elamur.ai/free/en/papers/taboada-2011-lexicon-based-methods-sentiment-analysis/)
9. [**Continual Lifelong Learning with Neural Networks: A Review**German I. Parisi, Ronald Kemker, Jose L. Part, et al.*2018 · 3,210 citations*](https://md.research.elamur.ai/free/en/papers/parisi-2018-continual-lifelong-learning-neural-networks/)
10. [**Exploring the Space of Topic Coherence Measures**Michael Röder, Andreas Both, Alexander Hinneburg*2015 · 2,368 citations*](https://md.research.elamur.ai/free/en/papers/roder-2015-exploring-space-topic-coherence-measures/)
11. [**chrF: character n-gram F-score for automatic MT evaluation**Maja Popović*2015 · 2,105 citations*](https://md.research.elamur.ai/free/en/papers/popovic-2015-chrf-character-n-gram-f/)
12. [**Knowledge Graphs**Aidan Hogan, Eva Blomqvist, Michael Cochez, et al.*2020 · 2,011 citations*](https://md.research.elamur.ai/free/en/papers/hogan-2020-knowledge-graphs/)
13. [**A Survey on Hate Speech Detection using Natural Language Processing**Anna Schmidt, Michael Wiegand*2017 · 1,799 citations*](https://md.research.elamur.ai/free/en/papers/schmidt-2017-survey-hate-speech-detection-natural/)
14. [**Exploiting Cloze-Questions for Few-Shot Text Classification and Natural Language Inference**Timo Schick, Hinrich Schütze*2021 · 1,796 citations*](https://md.research.elamur.ai/free/en/papers/schick-2021-exploiting-cloze-questions-few-shot/)
15. [**Attention-Based Models for Speech Recognition**Jan Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk, et al.*2015 · 1,776 citations*](https://md.research.elamur.ai/free/en/papers/chorowski-2015-attention-based-models-speech-recognition/)
16. [**TnT – A Statistical Part-of-Speech Tagger**Thorsten Brants*2000 · 1,756 citations*](https://md.research.elamur.ai/free/en/papers/brants-2000-tnt-statistical-part-speech-tagger/)
17. [**Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding**Akira Fukui, Dong Huk Park, Daylen Yang, et al.*2016 · 1,642 citations*](https://md.research.elamur.ai/free/en/papers/fukui-2016-multimodal-compact-bilinear-pooling-visual/)
18. [**How Can We Know What Language Models Know?**Zhengbao Jiang, Frank F. Xu, Jun Araki, et al.*2020 · 1,493 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2020-how-can-we-know-what/)
19. [**Improved Statistical Alignment Models**Franz Josef Och, Hermann Ney*2000 · 1,467 citations*](https://md.research.elamur.ai/free/en/papers/och-2000-improved-statistical-alignment-models/)
20. [**ELAN: a Professional Framework for Multimodality Research**Peter Wittenburg, Hennie Brugman, Albert Russel, et al.*2006 · 1,427 citations*](https://md.research.elamur.ai/free/en/papers/wittenburg-2006-elan-professional-framework-multimodality-research/)
21. [**Fast Graph Representation Learning with PyTorch Geometric**Matthias Fey, Jan Eric Lenssen*2019 · 1,413 citations*](https://md.research.elamur.ai/free/en/papers/fey-2019-fast-graph-representation-learning-pytorch/)
22. [**Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data**Emily M. Bender, Alexander Koller*2020 · 1,371 citations*](https://md.research.elamur.ai/free/en/papers/bender-2020-climbing-nlu-meaning-form-understanding/)
23. [**Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation**Nils Reimers, Iryna Gurevych*2020 · 1,320 citations*](https://md.research.elamur.ai/free/en/papers/reimers-2020-making-monolingual-sentence-embeddings-multilingual/)
24. [**It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners**Timo Schick, Hinrich Schütze*2021 · 1,118 citations*](https://md.research.elamur.ai/free/en/papers/schick-2021-it-s-not-just-size/)
25. [**ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs**Wenpeng Yin, Hinrich Schütze, Bing Xiang, et al.*2016 · 1,048 citations*](https://md.research.elamur.ai/free/en/papers/yin-2016-abcnn-attention-based-convolutional-neural/)

[See all 552 works →](https://md.research.elamur.ai/free/en/countries/germany/works/)

## Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

💡 Concepts 25[Transformer and attention · 3 works](https://md.research.elamur.ai/free/en/concepts/transformer/) · [BLEU score · 3 works](https://md.research.elamur.ai/free/en/concepts/bleu/) · [Language model · 1 work](https://md.research.elamur.ai/free/en/concepts/language-model/) · [Lexical semantics · 5 works](https://md.research.elamur.ai/free/en/concepts/lexical-semantics/) · [Part-of-speech tagging · 3 works](https://md.research.elamur.ai/free/en/concepts/part-of-speech-tagging/) · [Universal Dependencies · 3 works](https://md.research.elamur.ai/free/en/concepts/universal-dependencies/) · [Subword tokenization · 4 works](https://md.research.elamur.ai/free/en/concepts/subword-tokenization/) · [Semantic similarity · 2 works](https://md.research.elamur.ai/free/en/concepts/semantic-similarity/) · [Knowledge representation and reasoning · 3 works](https://md.research.elamur.ai/free/en/concepts/knowledge-representation/) · [Dependency parsing · 2 works](https://md.research.elamur.ai/free/en/concepts/dependency-parsing/) · [Corpus linguistics · 4 works](https://md.research.elamur.ai/free/en/concepts/corpus-linguistics/) · [Semantic role labeling · 2 works](https://md.research.elamur.ai/free/en/concepts/semantic-role-labeling/) · [Word embeddings · 1 work](https://md.research.elamur.ai/free/en/concepts/word-embeddings/) · [Scaling laws · 1 work](https://md.research.elamur.ai/free/en/concepts/scaling-laws/) · [Lexicography · 1 work](https://md.research.elamur.ai/free/en/concepts/lexicography/)+10 more

📚 Shelves 19[Linguistics & languages · 392 works](https://md.research.elamur.ai/free/en/shelves/linguistics/) · [Natural language processing · 149 works](https://md.research.elamur.ai/free/en/shelves/nlp/) · [Other · 22 works](https://md.research.elamur.ai/free/en/shelves/other/) · [Machine translation · 82 works](https://md.research.elamur.ai/free/en/shelves/machine-translation/) · [English · 101 works](https://md.research.elamur.ai/free/en/shelves/en/) · [AI & machine learning · 15 works](https://md.research.elamur.ai/free/en/shelves/ai/) · [Mathematics & statistics · 3 works](https://md.research.elamur.ai/free/en/shelves/mathematics/) · [Computing & GPUs · 7 works](https://md.research.elamur.ai/free/en/shelves/computing/) · [Education · 4 works](https://md.research.elamur.ai/free/en/shelves/education/) · [Machine translation · 26 works](https://md.research.elamur.ai/free/en/shelves/mtrans/) · [Law · 2 works](https://md.research.elamur.ai/free/en/shelves/law/) · [Vision, graphics & robotics · 1 work](https://md.research.elamur.ai/free/en/shelves/vision-robotics/) · [Society & ethics · 1 work](https://md.research.elamur.ai/free/en/shelves/society/) · [Semitic languages · 8 works](https://md.research.elamur.ai/free/en/shelves/sem/) · [Modern Hebrew · 4 works](https://md.research.elamur.ai/free/en/shelves/he/)+4 more

🧭 Topics 45[Machine translation · 55 works](https://md.research.elamur.ai/free/en/topics/machine-translation/) · [Coreference resolution · 79 works](https://md.research.elamur.ai/free/en/topics/coreference-resolution/) · [Language models & pretraining · 41 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Evaluation & benchmarks · 51 works](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Multilingual & cross-lingual NLP · 44 works](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/) · [Discourse analysis · 44 works](https://md.research.elamur.ai/free/en/topics/discourse-analysis/) · [Reasoning · 19 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Sentiment & emotion · 15 works](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) · [Dialogue systems · 20 works](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · [Question answering · 9 works](https://md.research.elamur.ai/free/en/topics/question-answering/) · [Semantic role labeling · 12 works](https://md.research.elamur.ai/free/en/topics/semantic-role-labeling/) · [Low-resource languages · 11 works](https://md.research.elamur.ai/free/en/topics/low-resource-languages/) · [Morphology · 15 works](https://md.research.elamur.ai/free/en/topics/morphology/) · [Vision & language · 5 works](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Part-of-speech tagging · 4 works](https://md.research.elamur.ai/free/en/topics/part-of-speech-tagging/)+30 more

## Works by year

### 2020s

[**2026** 47 works](https://md.research.elamur.ai/free/en/countries/germany/year/2026/) · [**2025** 19 works](https://md.research.elamur.ai/free/en/countries/germany/year/2025/) · [**2024** 20 works](https://md.research.elamur.ai/free/en/countries/germany/year/2024/) · [**2023** 43 works](https://md.research.elamur.ai/free/en/countries/germany/year/2023/) · [**2022** 26 works](https://md.research.elamur.ai/free/en/countries/germany/year/2022/) · [**2021** 45 works](https://md.research.elamur.ai/free/en/countries/germany/year/2021/) · [**2020** 47 works](https://md.research.elamur.ai/free/en/countries/germany/year/2020/)

### 2010s

[**2019** 26 works](https://md.research.elamur.ai/free/en/countries/germany/year/2019/) · [**2018** 47 works](https://md.research.elamur.ai/free/en/countries/germany/year/2018/) · [**2017** 43 works](https://md.research.elamur.ai/free/en/countries/germany/year/2017/) · [**2016** 29 works](https://md.research.elamur.ai/free/en/countries/germany/year/2016/) · [**2015** 15 works](https://md.research.elamur.ai/free/en/countries/germany/year/2015/) · [**2014** 18 works](https://md.research.elamur.ai/free/en/countries/germany/year/2014/) · [**2013** 13 works](https://md.research.elamur.ai/free/en/countries/germany/year/2013/) · [**2012** 26 works](https://md.research.elamur.ai/free/en/countries/germany/year/2012/) · [**2011** 11 works](https://md.research.elamur.ai/free/en/countries/germany/year/2011/) · [**2010** 15 works](https://md.research.elamur.ai/free/en/countries/germany/year/2010/)

### 2000s

[**2009** 7 works](https://md.research.elamur.ai/free/en/countries/germany/year/2009/) · [**2008** 9 works](https://md.research.elamur.ai/free/en/countries/germany/year/2008/) · [**2007** 3 works](https://md.research.elamur.ai/free/en/countries/germany/year/2007/) · [**2006** 12 works](https://md.research.elamur.ai/free/en/countries/germany/year/2006/) · [**2005** 1 work](https://md.research.elamur.ai/free/en/papers/matusov-2005-evaluating-machine-translation-output-automatic/) · [**2004** 7 works](https://md.research.elamur.ai/free/en/countries/germany/year/2004/) · [**2003** 1 work](https://md.research.elamur.ai/free/en/papers/strube-2003-machine-learning-approach-pronoun-resolution/) · [**2002** 1 work](https://md.research.elamur.ai/free/en/papers/butt-2002-parallel-grammar-project/) · [**2000** 5 works](https://md.research.elamur.ai/free/en/countries/germany/year/2000/)

### 1990s

[**1999** 3 works](https://md.research.elamur.ai/free/en/countries/germany/year/1999/) · [**1998** 4 works](https://md.research.elamur.ai/free/en/countries/germany/year/1998/) · [**1997** 1 work](https://md.research.elamur.ai/free/en/papers/skut-1997-annotation-scheme-free-word-order/) · [**1996** 1 work](https://md.research.elamur.ai/free/en/papers/hahn-1996-bridging-textual-ellipses/) · [**1995** 3 works](https://md.research.elamur.ai/free/en/countries/germany/year/1995/) · [**1994** 1 work](https://md.research.elamur.ai/free/en/papers/bos-1994-presupposition-vp-ellipsis/) · [**1993** 1 work](https://md.research.elamur.ai/free/en/papers/kay-1993-text-translation-alignment/)

### 1980s

[**1989** 2 works](https://md.research.elamur.ai/free/en/countries/germany/year/1989/)

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Updated 23 October 2026