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# Works of Switzerland

123 · page 1 of 2 · the most cited first · [← Switzerland](https://md.research.elamur.ai/free/en/countries/switzerland/)

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1. [**Array Programming with NumPy**Charles R. Harris, K. Jarrod Millman, Stéfan J. van der Walt, et al.*2020 · 23,591 citations*](https://md.research.elamur.ai/free/en/papers/harris-2020-array-programming-numpy/)
2. [**Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering**Michael Defferrard, Xavier Bresson, Pierre Vandergheynst*2016 · 1,797 citations*](https://md.research.elamur.ai/free/en/papers/defferrard-2016-convolutional-neural-networks-graphs-fast/)
3. [**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/)
4. [**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/)
5. [**Sigmoid Loss for Language Image Pre-Training**Xiaohua Zhai, Basil Mustafa, Alexander Kolesnikov, et al.*2023 · 1,427 citations*](https://md.research.elamur.ai/free/en/papers/zhai-2023-sigmoid-loss-language-image-pre/)
6. [**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/)
7. [**Unsupervised Learning of Sentence Embeddings Using Compositional n-Gram Features**Matteo Pagliardini, Prakhar Gupta, Martin Jaggi*2018 · 840 citations*](https://md.research.elamur.ai/free/en/papers/pagliardini-2018-unsupervised-learning-sentence-embeddings-compositional/)
8. [**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/)
9. [**Colorless Green Recurrent Networks Dream Hierarchically**Kristina Gulordava, Piotr Bojanowski, Edouard Grave, et al.*2018 · 759 citations*](https://md.research.elamur.ai/free/en/papers/gulordava-2018-colorless-green-recurrent-networks-dream/)
10. [**SoundStream: An End-to-End Neural Audio Codec**Neil Zeghidour, Alejandro Luebs, Ahmed Omran, et al.*2021 · 727 citations*](https://md.research.elamur.ai/free/en/papers/zeghidour-2021-soundstream-end-end-neural-audio/)
11. [**Neural Text Generation from Structured Data with Application to the Biography Domain**Remi Lebret, David Grangier, Michael Auli*2016 · 696 citations*](https://md.research.elamur.ai/free/en/papers/lebret-2016-neural-text-generation-structured-data/)
12. [**Learning Word Vectors for 157 Languages**Edouard Grave, Piotr Bojanowski, Prakhar Gupta, et al.*2018 · 640 citations*](https://md.research.elamur.ai/free/en/papers/grave-2018-learning-word-vectors-157-languages/)
13. [**Scalable Zero-shot Entity Linking with Dense Entity Retrieval**Ledell Wu, Fabio Petroni, Martin Josifoski, et al.*2020 · 618 citations*](https://md.research.elamur.ai/free/en/papers/wu-2020-scalable-zero-shot-entity-linking/)
14. [**AudioLM: a Language Modeling Approach to Audio Generation**Zalan Borsos, Raphael Marinier, Damien Vincent, et al.*2022 · 570 citations*](https://md.research.elamur.ai/free/en/papers/borsos-2022-audiolm-language-modeling-approach-audio/)
15. [**Fully Character-Level Neural Machine Translation without Explicit Segmentation**Jason Lee, Kyunghyun Cho, Thomas Hofmann*2017 · 545 citations*](https://md.research.elamur.ai/free/en/papers/lee-2017-fully-character-level-neural-machine/)
16. [**Multi-Source Transfer of Delexicalized Dependency Parsers**Ryan McDonald, Slav Petrov, Keith Hall*2011 · 490 citations*](https://md.research.elamur.ai/free/en/papers/mcdonald-2011-multi-source-transfer-delexicalized-dependency/)
17. [**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/)
18. [**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/)
19. [**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/)
20. [**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/)
21. [**Document-Level Neural Machine Translation with Hierarchical Attention Networks**Lesly Miculicich, Dhananjay Ram, Nikolaos Pappas, et al.*2018 · 411 citations*](https://md.research.elamur.ai/free/en/papers/miculicich-2018-document-level-neural-machine-translation/)
22. [**Identifying Word Translations in Non-Parallel Texts**Reinhard Rapp*1995 · 394 citations*](https://md.research.elamur.ai/free/en/papers/rapp-1995-identifying-word-translations-non-parallel/)
23. [**Reasoning with Latent Structure Refinement for Document-Level Relation Extraction**Guoshun Nan, Zhijiang Guo, Ivan Sekulic, et al.*2020 · 379 citations*](https://md.research.elamur.ai/free/en/papers/nan-2020-reasoning-latent-structure-refinement-document/)
24. [**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/)
25. [**Combining Distributional and Morphological Information for Part of Speech Induction**Alexander Clark*2003 · 295 citations*](https://md.research.elamur.ai/free/en/papers/clark-2003-combining-distributional-morphological-information-part/)
26. [**Information-Theoretic Probing for Linguistic Structure**Tiago Pimentel, Josef Valvoda, Rowan Hall Maudslay, et al.*2020 · 293 citations*](https://md.research.elamur.ai/free/en/papers/pimentel-2020-information-theoretic-probing-linguistic-structure/)
27. [**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/)
28. [**Abstractive Summarization of Product Reviews Using Discourse Structure**Shima Gerani, Yashar Mehdad, Giuseppe Carenini, et al.*2014 · 260 citations*](https://md.research.elamur.ai/free/en/papers/gerani-2014-abstractive-summarization-product-reviews-discourse/)
29. [**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/)
30. [**Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks**Rabeeh Karimi Mahabadi, Sebastian Ruder, Mostafa Dehghani, et al.*2021 · 248 citations*](https://md.research.elamur.ai/free/en/papers/mahabadi-2021-parameter-efficient-multi-task-fine/)
31. [**Transformers learn in-context by gradient descent**Johannes von Oswald, Eyvind Niklasson, Ettore Randazzo, et al.*2022 · 236 citations*](https://md.research.elamur.ai/free/en/papers/oswald-2022-transformers-learn-context-gradient-descent/)
32. [**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/)
33. [**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/)
34. [**Distilling Reasoning Capabilities into Smaller Language Models**Kumar Shridhar, Alessandro Stolfo, Mrinmaya Sachan*2023 · 216 citations*](https://md.research.elamur.ai/free/en/papers/shridhar-2023-distilling-reasoning-capabilities-into-smaller/)
35. [**Accelerating scientific discovery with Co-Scientist**Juraj Gottweis, Wei-Hung Weng, Alexander Daryin, et al.*2025 · 212 citations*](https://md.research.elamur.ai/free/en/papers/gottweis-2025-accelerating-scientific-discovery-co/)
36. [**Towards an ISO Standard for Dialogue Act Annotation**Harry Bunt, Jan Alexandersson, Jean Carletta, et al.*2010 · 210 citations*](https://md.research.elamur.ai/free/en/papers/bunt-2010-iso-standard-dialogue-act-annotation/)
37. [**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/)
38. [**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/)
39. [**Refusal in Language Models Is Mediated by a Single Direction**Andy Arditi, Oscar Obeso, Aaquib Syed, et al.*2024 · 188 citations*](https://md.research.elamur.ai/free/en/papers/arditi-2024-refusal-language-models-mediated-single/)
40. [**RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models**Zekun Moore Wang, Zhongyuan Peng, Haoran Que, et al.*2023 · 186 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-rolellm-benchmarking-eliciting-enhancing-role/)
41. [**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/)
42. [**ISO 24617-2: A semantically-based standard for dialogue annotation**Harry Bunt, Jan Alexandersson, Jae-Woong Choe, et al.*2012 · 182 citations*](https://md.research.elamur.ai/free/en/papers/bunt-2012-iso-24617-2-semantically-based/)
43. [**Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation**Shivalika Singh, Angelika Romanou, Clémentine Fourrier, et al.*2025 · 179 citations*](https://md.research.elamur.ai/free/en/papers/singh-2025-global-mmlu-understanding-addressing-cultural/)
44. [**Investigating Cultural Alignment of Large Language Models**Badr AlKhamissi, Muhammad ElNokrashy, Mai Alkhamissi, et al.*2024 · 177 citations*](https://md.research.elamur.ai/free/en/papers/alkhamissi-2024-investigating-cultural-alignment-large-language/)
45. [**Findings of the WMT24 General Machine Translation Shared Task: The LLM Era Is Here but MT Is Not Solved Yet**Tom Kocmi, Eleftherios Avramidis, Rachel Bawden, et al.*2024 · 177 citations*](https://md.research.elamur.ai/free/en/papers/kocmi-2024-findings-wmt24-general-machine-translation/)
46. [**Do Llamas Work in English? On the Latent Language of Multilingual Transformers**Chris Wendler, Veniamin Veselovsky, Giovanni Monea, et al.*2024 · 170 citations*](https://md.research.elamur.ai/free/en/papers/wendler-2024-do-llamas-work-english-latent/)
47. [**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/)
48. [**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/)
49. [**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/)
50. [**Testing the Predictions of Surprisal Theory in 11 Languages**Ethan G. Wilcox, Tiago Pimentel, Clara Meister, et al.*2023 · 158 citations*](https://md.research.elamur.ai/free/en/papers/wilcox-2023-testing-predictions-surprisal-theory-11/)
51. [**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/)
52. [**Locally Typical Sampling**Clara Meister, Tiago Pimentel, Gian Wiher, et al.*2023 · 152 citations*](https://md.research.elamur.ai/free/en/papers/meister-2023-locally-typical-sampling/)
53. [**REFINER: Reasoning Feedback on Intermediate Representations**Debjit Paul, Mete Ismayilzada, Maxime Peyrard, et al.*2023 · 152 citations*](https://md.research.elamur.ai/free/en/papers/paul-2023-refiner-reasoning-feedback-intermediate-representations/)
54. [**Agent Laboratory: Using LLM Agents as Research Assistants**Samuel Schmidgall, Yusheng Su, Ze Wang, et al.*2025 · 136 citations*](https://md.research.elamur.ai/free/en/papers/schmidgall-2025-agent-laboratory-using-llm/)
55. [**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/)
56. [**MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning Problems**Jakub Macina, Nico Daheim, Sankalan Chowdhury, et al.*2023 · 130 citations*](https://md.research.elamur.ai/free/en/papers/macina-2023-mathdial-dialogue-tutoring-dataset-rich/)
57. [**Swiss-Judgment-Prediction: A Multilingual Legal Judgment Prediction Benchmark**Joel Niklaus, Ilias Chalkidis, Matthias Stürmer*2021 · 129 citations*](https://md.research.elamur.ai/free/en/papers/niklaus-2021-swiss-judgment-prediction-multilingual-legal/)
58. [**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/)
59. [**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/)
60. [**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/)
61. [**End-to-End Bias Mitigation by Modelling Biases in Corpora**Rabeeh Karimi Mahabadi, Yonatan Belinkov, James Henderson*2020 · 107 citations*](https://md.research.elamur.ai/free/en/papers/mahabadi-2020-end-end-bias-mitigation-modelling/)
62. [**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/)
63. [**Using Test Suites in Evaluation of Machine Translation Systems**Margaret King, Kirsten Falkedal*1990 · 95 citations*](https://md.research.elamur.ai/free/en/papers/king-1990-test-suites-evaluation-machine-translation/)
64. [**Using Sense-labeled Discourse Connectives for Statistical Machine Translation**Thomas Meyer, Andrei Popescu-Belis*2012 · 93 citations*](https://md.research.elamur.ai/free/en/papers/meyer-2012-sense-labeled-discourse-connectives-statistical/)
65. [**Validation of an Automatic Metric for the Accuracy of Pronoun Translation (APT)**Lesly Miculicich Werlen, Andrei Popescu-Belis*2017 · 86 citations*](https://md.research.elamur.ai/free/en/papers/werlen-2017-validation-automatic-metric-accuracy-pronoun/)
66. [**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/)
67. [**Error Span Annotation: A Balanced Approach for Human Evaluation of Machine Translation**Tom Kocmi, Vilém Zouhar, Eleftherios Avramidis, et al.*2024 · 83 citations*](https://md.research.elamur.ai/free/en/papers/kocmi-2024-error-span-annotation-balanced-approach/)
68. [**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/)
69. [**Implicitation of Discourse Connectives in (Machine) Translation**Thomas Meyer, Bonnie Webber*2013 · 80 citations*](https://md.research.elamur.ai/free/en/papers/meyer-2013-implicitation-discourse-connectives-machine-translation/)
70. [**The Notion of Argument in Prepositional Phrase Attachment**Paola Merlo, Eva Esteve Ferrer*2006 · 75 citations*](https://md.research.elamur.ai/free/en/papers/merlo-2006-notion-argument-prepositional-phrase-attachment/)
71. [**Findings of the WMT25 General Machine Translation Shared Task: Time to Stop Evaluating on Easy Test Sets**Tom Kocmi, Ekaterina Artemova, Eleftherios Avramidis, et al.*2025 · 73 citations*](https://md.research.elamur.ai/free/en/papers/kocmi-2025-findings-wmt25-general-machine-translation/)
72. [**The SIGMORPHON 2022 Shared Task on Morpheme Segmentation**Khuyagbaatar Batsuren, Gabor Bella, Aryaman Arora*2022 · 71 citations*](https://md.research.elamur.ai/free/en/papers/batsuren-2022-morpheme-segmentation/)
73. [**Annotating the meaning of discourse connectives by looking at their translation: The translation-spotting technique**Bruno Cartoni, Sandrine Zufferey, Thomas Meyer*2013 · 69 citations*](https://md.research.elamur.ai/free/en/papers/cartoni-2013-annotating-meaning-discourse-connectives-looking/)
74. [**Machine Translation of Labeled Discourse Connectives**Thomas Meyer, Andrei Popescu-Belis, Najeh Hajlaoui, et al.*2012 · 55 citations*](https://md.research.elamur.ai/free/en/papers/meyer-2012-machine-translation-labeled-discourse-connectives/)
75. [**Multi-level Dialogue Act Tags**Alexander Clark, Andrei Popescu-Belis*2004 · 54 citations*](https://md.research.elamur.ai/free/en/papers/clark-2004-multi-level-dialogue-act-tags/)
76. [**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/)
77. [**Lemmatisation as a Tagging Task**Andrea Gesmundo, Tanja Samardžić*2012 · 47 citations*](https://md.research.elamur.ai/free/en/papers/gesmundo-2012-lemmatisation-as-tagging-task/)
78. [**Abstraction and Generalisation in Semantic Role Labels: PropBank, VerbNet or both?**Paola Merlo, Lonneke van der Plas*2009 · 45 citations*](https://md.research.elamur.ai/free/en/papers/merlo-2009-abstraction-generalisation-semantic-role-labels/)
79. [**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/)
80. [**Automatic Prediction of Discourse Connectives**Eric Malmi, Daniele Pighin, Sebastian Krause, et al.*2018 · 38 citations*](https://md.research.elamur.ai/free/en/papers/malmi-2018-automatic-prediction-discourse-connectives/)
81. [**No case for Case in locality: Case does not help interpretation when intervention blocks A-bar chains**Naama Friedmann, Luigi Rizzi, Adriana Belletti*2017 · 37 citations*](https://md.research.elamur.ai/free/en/papers/friedmann-2017-no-case-case-locality-case/)
82. [**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/)
83. [**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/)
84. [**Fine-Tuned Machine Translation Metrics Struggle in Unseen Domains**Vilém Zouhar, Shuoyang Ding, Anna Currey, et al.*2024 · 32 citations*](https://md.research.elamur.ai/free/en/papers/zouhar-2024-fine-tuned-machine-translation-metrics/)
85. [**Factors Influencing the Implicitation of Discourse Relations across Languages**Jet Hoek, Sandrine Zufferey*2015 · 30 citations*](https://md.research.elamur.ai/free/en/papers/hoek-2015-factors-influencing-implicitation-discourse-relations/)
86. [**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/)
87. [**Context Matters: A Pragmatic Study of PLMs' Negation Understanding**Reto Gubelmann, Siegfried Handschuh*2022 · 28 citations*](https://md.research.elamur.ai/free/en/papers/gubelmann-2022-context-matters-pragmatic-study-plms/)
88. [**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/)
89. [**Recursive Non-Autoregressive Graph-to-Graph Transformer for Dependency Parsing with Iterative Refinement**Alireza Mohammadshahi, James Henderson*2021 · 26 citations*](https://md.research.elamur.ai/free/en/papers/mohammadshahi-2021-recursive-non-autoregressive-graph-graph/)
90. [**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/)
91. [**Annotating tense, mood and voice for English, French and German**Anita Ramm, Sharid Loáiciga, Annemarie Friedrich, et al.*2017 · 25 citations*](https://md.research.elamur.ai/free/en/papers/ramm-2017-annotating-tense-mood-voice-english/)
92. [**Machine Translation with Many Manually Labeled Discourse Connectives**Thomas Meyer, Lucie Poláková*2013 · 24 citations*](https://md.research.elamur.ai/free/en/papers/meyer-2013-machine-translation-many-manually-labeled/)
93. [**Scaling Within Document Coreference to Long Texts**Raghuveer Thirukovalluru, Nicholas Monath, Kumar Shridhar, et al.*2021 · 24 citations*](https://md.research.elamur.ai/free/en/papers/thirukovalluru-2021-scaling-within-document-coreference-long/)
94. [**Using Coreference Links to Improve Spanish-to-English Machine Translation**Lesly Miculicich Werlen, Andrei Popescu-Belis*2017 · 24 citations*](https://md.research.elamur.ai/free/en/papers/werlen-2017-coreference-links-improve-spanish-english/)
95. [**Graph-to-Graph Transformer for Transition-based Dependency Parsing**Alireza Mohammadshahi, James Henderson*2020 · 23 citations*](https://md.research.elamur.ai/free/en/papers/mohammadshahi-2020-graph-graph-transformer-transition-based/)
96. [**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/)
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