---
title: "University of Zurich — works"
description: "44 works by researchers of University of Zurich in our library, the most cited first."
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---
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# Works of University of Zurich

44 works · the most cited first · [← University of Zurich](https://md.research.elamur.ai/free/en/universities/university-of-zurich/)

1. [**ChatGPT Outperforms Crowd-Workers for Text-Annotation Tasks**Fabrizio Gilardi, Meysam Alizadeh, Maël Kubli*2023 · 1,532 citations*](https://md.research.elamur.ai/free/en/papers/gilardi-2023-chatgpt-outperforms-crowd-workers-text/)
2. [**Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned**Elena Voita, David Talbot, Fedor Moiseev, et al.*2019 · 1,511 citations*](https://md.research.elamur.ai/free/en/papers/voita-2019-analyzing-multi-head-self-attention/)
3. [**Adapted Large Language Models Can Outperform Medical Experts in Clinical Text Summarization**Dave Van Veen, Cara Van Uden, Louis Blankemeier, et al.*2023 · 925 citations*](https://md.research.elamur.ai/free/en/papers/veen-2023-adapted-large-language-models-outperform/)
4. [**Findings of the 2019 Conference on Machine Translation (WMT19)**Loïc Barrault, Ondřej Bojar, Marta R. Costa-jussà, et al.*2019 · 839 citations*](https://md.research.elamur.ai/free/en/papers/barrault-2019-findings-2019-conference-machine-translation/)
5. [**Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation**Biao Zhang, Philip Williams, Ivan Titov, et al.*2020 · 472 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2020-improving-massively-multilingual-neural-machine/)
6. [**Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets**Julia Kreutzer, Isaac Caswell, Lisa Wang, et al.*2021 · 447 citations*](https://md.research.elamur.ai/free/en/papers/kreutzer-2021-quality-glance-audit-web-crawled/)
7. [**Context-Aware Neural Machine Translation Learns Anaphora Resolution**Elena Voita, Pavel Serdyukov, Rico Sennrich, et al.*2018 · 446 citations*](https://md.research.elamur.ai/free/en/papers/voita-2018-context-aware-neural-machine-translation/)
8. [**Has Machine Translation Achieved Human Parity? A Case for Document-level Evaluation**Samuel Läubli, Rico Sennrich, Martin Volk*2018 · 443 citations*](https://md.research.elamur.ai/free/en/papers/laubli-2018-has-machine-translation-achieved-human/)
9. [**When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical Cohesion**Elena Voita, Rico Sennrich, Ivan Titov*2019 · 321 citations*](https://md.research.elamur.ai/free/en/papers/voita-2019-when-good-translation-is-wrong/)
10. [**Findings of the VarDial Evaluation Campaign 2017**Marcos Zampieri, Shervin Malmasi, Nikola Ljubešić, et al.*2017 · 261 citations*](https://md.research.elamur.ai/free/en/papers/zampieri-2017-findings-vardial-evaluation-campaign/)
11. [**Evaluating Discourse Phenomena in Neural Machine Translation**Rachel Bawden, Rico Sennrich, Alexandra Birch, et al.*2017 · 252 citations*](https://md.research.elamur.ai/free/en/papers/bawden-2017-evaluating-discourse-phenomena-neural-machine/)
12. [**Humanity's Last Exam**Long Phan, Alice Gatti, Ziwen Han, et al.*2025 · 235 citations*](https://md.research.elamur.ai/free/en/papers/phan-2025-humanity-s-last-exam/)
13. [**The Bottom-up Evolution of Representations in the Transformer: A Study with Machine Translation and Language Modeling Objectives**Elena Voita, Rico Sennrich, Ivan Titov*2019 · 222 citations*](https://md.research.elamur.ai/free/en/papers/voita-2019-bottom-up-evolution-representations-transformer/)
14. [**On Exposure Bias, Hallucination and Domain Shift in Neural Machine Translation**Chaojun Wang, Rico Sennrich*2020 · 204 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-exposure-bias-hallucination-domain-shift/)
15. [**Nematus: a Toolkit for Neural Machine Translation**Rico Sennrich, Orhan Firat, Kyunghyun Cho, et al.*2017 · 202 citations*](https://md.research.elamur.ai/free/en/papers/sennrich-2017-nematus-toolkit-neural-machine-translation/)
16. [**Improving Word Sense Disambiguation in Neural Machine Translation with Sense Embeddings**Annette Rios Gonzales, Laura Mascarell, Rico Sennrich*2017 · 185 citations*](https://md.research.elamur.ai/free/en/papers/gonzales-2017-improving-word-sense-disambiguation-neural/)
17. [**Language Identification and Morphosyntactic Tagging: The Second VarDial Evaluation Campaign**Marcos Zampieri, Shervin Malmasi, Preslav Nakov, et al.*2018 · 169 citations*](https://md.research.elamur.ai/free/en/papers/zampieri-2018-language-identification-morphosyntactic-tagging-second/)
18. [**Dirt Cheap Web-Scale Parallel Text from the Common Crawl**Jason R. Smith, Herve Saint-Amand, Magdalena Plamada, et al.*2013 · 165 citations*](https://md.research.elamur.ai/free/en/papers/smith-2013-dirt-cheap-web-scale-parallel/)
19. [**AmericasNLI: Evaluating Zero-shot Natural Language Understanding of Pretrained Multilingual Models in Truly Low-resource Languages**Abteen Ebrahimi, Manuel Mager, Arturo Oncevay, et al.*2022 · 163 citations*](https://md.research.elamur.ai/free/en/papers/ebrahimi-2022-americasnli-evaluating-zero-shot-natural/)
20. [**CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claims**Thomas Diggelmann, Jordan Boyd-Graber, Jannis Bulian, et al.*2020 · 157 citations*](https://md.research.elamur.ai/free/en/papers/diggelmann-2020-climate-fever-dataset-verification-real/)
21. [**Domain Robustness in Neural Machine Translation**Mathias Müller, Annette Rios, Rico Sennrich*2020 · 135 citations*](https://md.research.elamur.ai/free/en/papers/muller-2020-domain-robustness-neural-machine-translation/)
22. [**A Large-Scale Test Set for the Evaluation of Context-Aware Pronoun Translation in Neural Machine Translation**Mathias Müller, Annette Rios, Elena Voita, et al.*2018 · 123 citations*](https://md.research.elamur.ai/free/en/papers/muller-2018-large-scale-test-set-evaluation/)
23. [**LEXTREME: A Multi-Lingual and Multi-Task Benchmark for the Legal Domain**Joel Niklaus, Veton Matoshi, Pooja Rani, et al.*2023 · 122 citations*](https://md.research.elamur.ai/free/en/papers/niklaus-2023-lextreme-multi-lingual-multi-task/)
24. [**Findings of the AmericasNLP 2021 Shared Task on Open Machine Translation for Indigenous Languages of the Americas**Manuel Mager, Arturo Oncevay, Abteen Ebrahimi, et al.*2021 · 118 citations*](https://md.research.elamur.ai/free/en/papers/mager-2021-findings-americasnlp-2021-shared-task/)
25. [**LEDGAR: A Large-Scale Multi-label Corpus for Text Classification of Legal Provisions in Contracts**Don Tuggener, Pius von Däniken, Thomas Peetz, et al.*2020 · 107 citations*](https://md.research.elamur.ai/free/en/papers/tuggener-2020-ledgar-large-scale-multi-label/)
26. [**BlonDe: An Automatic Evaluation Metric for Document-level Machine Translation**Yuchen Jiang, Tianyu Liu, Shuming Ma, et al.*2022 · 85 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2022-blonde-automatic-evaluation-metric-document/)
27. [**UniMorph 4.0: Universal Morphology**Khuyagbaatar Batsuren, Omer Goldman, Salam Khalifa*2022 · 82 citations*](https://md.research.elamur.ai/free/en/papers/batsuren-2022-unimorph-4/)
28. [**Speech act attenuation in the history of English: The case of apologies**Andreas H. Jucker*2019 · 54 citations*](https://md.research.elamur.ai/free/en/papers/jucker-2019-speech-act-attenuation-history-english/)
29. [**Findings of the Second WMT Shared Task on Sign Language Translation (WMT-SLT23)**Mathias Müller, Malihe Alikhani, Eleftherios Avramidis, et al.*2023 · 39 citations*](https://md.research.elamur.ai/free/en/papers/muller-2023-findings-second-wmt-shared-task/)
30. [**Combining Unsupervised and Supervised Methods for PP Attachment Disambiguation**Martin Volk*2002 · 34 citations*](https://md.research.elamur.ai/free/en/papers/volk-2002-combining-unsupervised-supervised-methods-pp/)
31. [**Wino-X: Multilingual Winograd Schemas for Commonsense Reasoning and Coreference Resolution**Denis Emelin, Rico Sennrich*2021 · 34 citations*](https://md.research.elamur.ai/free/en/papers/emelin-2021-wino-x-multilingual-winograd-schemas/)
32. [**ACES: Translation Accuracy Challenge Sets for Evaluating Machine Translation Metrics**Chantal Amrhein, Nikita Moghe, Liane Guillou*2022 · 29 citations*](https://md.research.elamur.ai/free/en/papers/amrhein-2022-aces-translation-accuracy-challenge-sets/)
33. [**Machine Translation Meta Evaluation through Translation Accuracy Challenge Sets**Nikita Moghe, Arnisa Fazla, Chantal Amrhein, et al.*2025 · 28 citations*](https://md.research.elamur.ai/free/en/papers/moghe-2025-machine-translation-meta-evaluation-through/)
34. [**An Incremental Entity-Mention Model for Coreference Resolution with Restrictive Antecedent Accessibility**Manfred Klenner, Don Tuggener*2011 · 25 citations*](https://md.research.elamur.ai/free/en/papers/klenner-2011-incremental-entity-mention-model-coreference/)
35. [**Coreference Resolution Evaluation for Higher Level Applications**Don Tuggener*2014 · 23 citations*](https://md.research.elamur.ai/free/en/papers/tuggener-2014-coreference-resolution-evaluation-higher-level/)
36. [**Automatic MT Error Analysis: Hjerson Helping Addicter**Jan Berka, Ondřej Bojar, Mark Fishel, et al.*2012 · 17 citations*](https://md.research.elamur.ai/free/en/papers/berka-2012-automatic-mt-error-analysis-hjerson/)
37. [**Comparing Rule-based and SMT-based Spelling Normalisation for English Historical Texts**Gerold Schneider, Eva Pettersson, Michael Percillier*2017 · 15 citations*](https://md.research.elamur.ai/free/en/papers/schneider-2017-comparing-rule-based-smt-based/)
38. [**Semi-supervised Contextual Historical Text Normalization**Peter Makarov, Simon Clematide*2020 · 12 citations*](https://md.research.elamur.ai/free/en/papers/makarov-2020-semi-supervised-contextual-historical-text/)
39. [**Optimizing the Size of Subword Vocabularies in Dialect Classification**Vani Kanjirangat, Tanja Samardžić, Ljiljana Dolamic, et al.*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/kanjirangat-2023-optimizing-size-subword-vocabularies-dialect/)
40. [**Arabic Speech Rhythm Corpus: Read and Spontaneous Speaking Styles**Omnia Ibrahim, Homa Asadi, Eman Kassem, et al.*2020 · 4 citations*](https://md.research.elamur.ai/free/en/papers/ibrahim-2020-arabic-speech-rhythm-corpus-read/)
41. [**Few-Shot and Zero-Shot Learning for Historical Text Normalization**Marcel Bollmann, Natalia Korchagina, Anders Søgaard*2019 · 2 citations*](https://md.research.elamur.ai/free/en/papers/bollmann-2019-few-shot-zero-shot-learning/)
42. [**Ranking Translations using Error Analysis and Quality Estimation**Mark Fishel*2013 · 2 citations*](https://md.research.elamur.ai/free/en/papers/fishel-2013-ranking-translations-error-analysis-quality/)
43. [**Towards an Integrated Methodology of Dating Biblical Texts: The Case of the Book of Jeremiah**Martijn Naaijer, Aren Wilson-Wright*2025*](https://md.research.elamur.ai/free/en/papers/naaijer-2025-integrated-methodology-dating-biblical-texts/)
44. [**Identifying Phrase Boundaries in the Samaritan Pentateuch with Machine Learning**Saulo de Oliveira Cantanhede, Martijn Naaijer, Christian Canu Højgaard, et al.*2026*](https://md.research.elamur.ai/free/en/papers/cantanhede-2026-identifying-phrase-boundaries-samaritan-pentateuch/)
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