---
title: "Denmark — works"
description: "Works of Denmark: 79 in our library, the most cited first."
canonical: "https://research.elamur.ai/free/en/countries/denmark/works/"
---
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# Works of Denmark

79 · the most cited first · [← Denmark](https://md.research.elamur.ai/free/en/countries/denmark/)

1. [**Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter**Zeerak Waseem, Dirk Hovy*2016 · 2,158 citations*](https://md.research.elamur.ai/free/en/papers/waseem-2016-hateful-symbols-or-hateful-people/)
2. [**A Primer in BERTology: What We Know About How BERT Works**Anna Rogers, Olga Kovaleva, Anna Rumshisky*2020 · 2,127 citations*](https://md.research.elamur.ai/free/en/papers/rogers-2020-primer-bertology-what-we-know/)
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. [**Are You a Racist or Am I Seeing Things? Annotator Influence on Hate Speech Detection on Twitter**Zeerak Waseem*2016 · 760 citations*](https://md.research.elamur.ai/free/en/papers/waseem-2016-are-you-racist-or-am/)
5. [**Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm**Bjarke Felbo, Alan Mislove, Anders Søgaard, et al.*2017 · 617 citations*](https://md.research.elamur.ai/free/en/papers/felbo-2017-millions-emoji-occurrences-learn-any/)
6. [**Deep multi-task learning with low level tasks supervised at lower layers**Anders Søgaard, Yoav Goldberg*2016 · 584 citations*](https://md.research.elamur.ai/free/en/papers/sogaard-2016-deep-multi-task-learning-low/)
7. [**The Social Impact of Natural Language Processing**Dirk Hovy, Shannon L. Spruit*2016 · 516 citations*](https://md.research.elamur.ai/free/en/papers/hovy-2016-social-impact-natural-language-processing/)
8. [**On the Limitations of Unsupervised Bilingual Dictionary Induction**Anders Søgaard, Sebastian Ruder, Ivan Vulić*2018 · 396 citations*](https://md.research.elamur.ai/free/en/papers/sogaard-2018-limitations-unsupervised-bilingual-dictionary-induction/)
9. [**JW300: A Wide-Coverage Parallel Corpus for Low-Resource Languages**Željko Agić, Ivan Vulić*2019 · 373 citations*](https://md.research.elamur.ai/free/en/papers/agic-2019-jw300-wide-coverage-parallel-corpus/)
10. [**Neural Unsupervised Domain Adaptation in NLP–-A Survey**Alan Ramponi, Barbara Plank*2020 · 334 citations*](https://md.research.elamur.ai/free/en/papers/ramponi-2020-neural-unsupervised-domain-adaptation-nlp/)
11. [**MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims**Isabelle Augenstein, Christina Lioma, Dongsheng Wang, et al.*2019 · 318 citations*](https://md.research.elamur.ai/free/en/papers/augenstein-2019-multifc-real-world-multi-domain/)
12. [**Identifying beneficial task relations for multi-task learning in deep neural networks**Joachim Bingel, Anders Søgaard*2017 · 305 citations*](https://md.research.elamur.ai/free/en/papers/bingel-2017-identifying-beneficial-task-relations-multi/)
13. [**SemEval-2019 Task 7: RumourEval, Determining Rumour Veracity and Support for Rumours**Genevieve Gorrell, Elena Kochkina, Maria Liakata, et al.*2019 · 290 citations*](https://md.research.elamur.ai/free/en/papers/gorrell-2019-semeval-2019-task-7-rumoureval/)
14. [**Challenges and Strategies in Cross-Cultural NLP**Daniel Hershcovich, Stella Frank, Heather Lent, et al.*2022 · 290 citations*](https://md.research.elamur.ai/free/en/papers/hershcovich-2022-challenges-strategies-cross-cultural-nlp/)
15. [**Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Study**Yong Cao, Li Zhou, Seolhwa Lee, et al.*2023 · 278 citations*](https://md.research.elamur.ai/free/en/papers/cao-2023-assessing-cross-cultural-alignment-between/)
16. [**A Diagnostic Study of Explainability Techniques for Text Classification**Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma, et al.*2020 · 273 citations*](https://md.research.elamur.ai/free/en/papers/atanasova-2020-diagnostic-study-explainability-techniques-text/)
17. [**LexGLUE: A Benchmark Dataset for Legal Language Understanding in English**Ilias Chalkidis; Abhik Jana; Dirk Hartung; Michael Bommarito; Ion Androutsopoulos; Daniel Martin Katz;, Nikolaos Aletras*2021 · 256 citations*](https://md.research.elamur.ai/free/en/papers/chalkidis-2021-lexglue-benchmark-dataset-legal-language/)
18. [**Factuality Challenges in the Era of Large Language Models**Isabelle Augenstein, Timothy Baldwin, Meeyoung Cha, et al.*2023 · 241 citations*](https://md.research.elamur.ai/free/en/papers/augenstein-2023-factuality-challenges-era-large-language/)
19. [**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/)
20. [**Findings of the Third Shared Task on Multimodal Machine Translation**Loïc Barrault, Fethi Bougares, Lucia Specia, et al.*2018 · 227 citations*](https://md.research.elamur.ai/free/en/papers/barrault-2018-findings-third-shared-task-multimodal/)
21. [**Generating Fact Checking Explanations**Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma, et al.*2020 · 219 citations*](https://md.research.elamur.ai/free/en/papers/atanasova-2020-generating-fact-checking-explanations/)
22. [**Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning**Shivalika Singh, Freddie Vargus, Daniel D'souza, et al.*2024 · 202 citations*](https://md.research.elamur.ai/free/en/papers/singh-2024-aya-dataset-open-access-collection/)
23. [**Multilingual Part-of-Speech Tagging with Bidirectional Long Short-Term Memory Models and Auxiliary Loss**Barbara Plank, Anders Søgaard, Yoav Goldberg*2016 · 201 citations*](https://md.research.elamur.ai/free/en/papers/plank-2016-multilingual-part-speech-tagging-bidirectional/)
24. [**Multilingual Projection for Parsing Truly Low-Resource Languages**Željko Agić, Anders Johannsen, Barbara Plank, et al.*2016 · 195 citations*](https://md.research.elamur.ai/free/en/papers/agic-2016-multilingual-projection-parsing-truly-low/)
25. [**A Survey on Stance Detection for Mis- and Disinformation Identification**Momchil Hardalov, Arnav Arora, Preslav Nakov, et al.*2022 · 187 citations*](https://md.research.elamur.ai/free/en/papers/hardalov-2022-survey-stance-detection-mis-disinformation/)
26. [**We Need to Consider Disagreement in Evaluation**Valerio Basile, Michael Fell, Tommaso Fornaciari, et al.*2021 · 185 citations*](https://md.research.elamur.ai/free/en/papers/basile-2021-we-need-consider-disagreement-evaluation/)
27. [**Massive Choice, Ample Tasks (MaChAmp): A Toolkit for Multi-task Learning in NLP**Rob van der Goot, Ahmet Üstün, Alan Ramponi, et al.*2021 · 177 citations*](https://md.research.elamur.ai/free/en/papers/goot-2021-massive-choice-ample-tasks-machamp/)
28. [**MultiEURLEX - A multi-lingual and multi-label legal document classification dataset for zero-shot cross-lingual transfer**Ilias Chalkidis, Manos Fergadiotis, Ion Androutsopoulos*2021 · 160 citations*](https://md.research.elamur.ai/free/en/papers/chalkidis-2021-multieurlex-multi-lingual-multi-label/)
29. [**Probing Pre-Trained Language Models for Cross-Cultural Differences in Values**Arnav Arora, Lucie-aimée Kaffee, Isabelle Augenstein*2023 · 155 citations*](https://md.research.elamur.ai/free/en/papers/arora-2023-probing-pre-trained-language-models/)
30. [**The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset**Hugo Laurençon, Lucile Saulnier, Thomas Wang, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2023-bigscience-roots-corpus-1-6tb/)
31. [**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/)
32. [**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/)
33. [**Offensive Language and Hate Speech Detection for Danish**Gudbjartur Ingi Sigurbergsson, Leon Derczynski*2020 · 106 citations*](https://md.research.elamur.ai/free/en/papers/sigurbergsson-2020-offensive-language-hate-speech-detection/)
34. [**Learning How to Simplify From Explicit Labeling of Complex-Simplified Text Pairs**Fernando Alva-Manchego, Joachim Bingel, Gustavo Paetzold, et al.*2017 · 104 citations*](https://md.research.elamur.ai/free/en/papers/manchego-2017-learning-how-simplify-explicit-labeling/)
35. [**SemEval-2016 Task 10: Detecting Minimal Semantic Units and their Meanings (DiMSUM)**Nathan Schneider, Dirk Hovy, Anders Johannsen, et al.*2016 · 100 citations*](https://md.research.elamur.ai/free/en/papers/schneider-2016-semeval-2016-task-10-detecting/)
36. [**A Large-Scale Comparison of Historical Text Normalization Systems**Marcel Bollmann*2019 · 99 citations*](https://md.research.elamur.ai/free/en/papers/bollmann-2019-large-scale-comparison-historical-text/)
37. [**Cross-Domain Label-Adaptive Stance Detection**Momchil Hardalov, Arnav Arora, Preslav Nakov, et al.*2021 · 96 citations*](https://md.research.elamur.ai/free/en/papers/hardalov-2021-cross-domain-label-adaptive-stance/)
38. [**Automatic training of lemmatization rules that handle morphological changes in pre-, in- and suffixes alike**Bart Jongejan, Hercules Dalianis*2009 · 90 citations*](https://md.research.elamur.ai/free/en/papers/jongejan-2009-automatic-training-lemmatization-rules-that/)
39. [**Putting Sarcasm Detection into Context: The Effects of Class Imbalance and Manual Labelling on Supervised Machine Classification of Twitter Conversations**Gavin Abercrombie, Dirk Hovy*2016 · 85 citations*](https://md.research.elamur.ai/free/en/papers/abercrombie-2016-putting-sarcasm-detection-into-context/)
40. [**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/)
41. [**Multi-view and multi-task training of RST discourse parsers**Chloé Braud, Barbara Plank, Anders Søgaard*2016 · 67 citations*](https://md.research.elamur.ai/free/en/papers/braud-2016-multi-view-multi-task-training/)
42. [**Annotating Information Structure in a Corpus of Spoken Danish**Patrizia Paggio*2006 · 61 citations*](https://md.research.elamur.ai/free/en/papers/paggio-2006-annotating-information-structure-corpus-spoken/)
43. [**Learning a POS tagger for AAVE-like language**Anna Jørgensen, Dirk Hovy, Anders Søgaard*2016 · 59 citations*](https://md.research.elamur.ai/free/en/papers/jorgensen-2016-learning-pos-tagger-aave-like/)
44. [**Learning Connective-based Word Representations for Implicit Discourse Relation Identification**Chloé Braud, Pascal Denis*2016 · 56 citations*](https://md.research.elamur.ai/free/en/papers/braud-2016-learning-connective-based-word-representations/)
45. [**Learning attention for historical text normalization by learning to pronounce**Marcel Bollmann, Joachim Bingel, Anders Søgaard*2017 · 47 citations*](https://md.research.elamur.ai/free/en/papers/bollmann-2017-learning-attention-historical-text-normalization/)
46. [**Cross-Lingual Parser Selection for Low-Resource Languages**Željko Agić*2017 · 46 citations*](https://md.research.elamur.ai/free/en/papers/agic-2017-cross-lingual-parser-selection-low/)
47. [**What Does Your Smile Mean? Jointly Detecting Multi-Modal Sarcasm and Sentiment Using Quantum Probability**Yaochen Liu, Yazhou Zhang, Qiuchi Li, et al.*2021 · 43 citations*](https://md.research.elamur.ai/free/en/papers/liu-2021-what-does-your-smile-mean/)
48. [**Is Sarcasm Detection A Step-by-Step Reasoning Process in Large Language Models?**Ben Yao, Yazhou Zhang, Qiuchi Li, et al.*2024 · 33 citations*](https://md.research.elamur.ai/free/en/papers/yao-2024-sarcasm-detection-step-step-reasoning/)
49. [**Multi-task learning for historical text normalization: Size matters**Marcel Bollmann, Anders Søgaard, Joachim Bingel*2018 · 24 citations*](https://md.research.elamur.ai/free/en/papers/bollmann-2018-multi-task-learning-historical-text/)
50. [**Exemplification Modeling: Can You Give Me an Example, Please?**Edoardo Barba, Luigi Procopio, Caterina Lacerra*2021 · 23 citations*](https://md.research.elamur.ai/free/en/papers/barba-2021-exemplification-modeling/)
51. [**Dating ancient manuscripts using radiocarbon and AI-based writing style analysis**Mladen Popovic, Maruf A. Dhali, Lambert Schomaker, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/popovic-2024-dating-ancient-manuscripts-using-radiocarbon/)
52. [**Topic-Guided Sampling For Data-Efficient Multi-Domain Stance Detection**Erik Arakelyan, Arnav Arora, Isabelle Augenstein*2023 · 19 citations*](https://md.research.elamur.ai/free/en/papers/arakelyan-2023-topic-guided-sampling-data-efficient/)
53. [**Ellipsis Resolution as Question Answering: An Evaluation**Rahul Aralikatte, Matthew Lamm, Daniel Hardt, et al.*2021 · 19 citations*](https://md.research.elamur.ai/free/en/papers/aralikatte-2021-ellipsis-resolution-as-question-answering/)
54. [**Improving historical spelling normalization with bi-directional LSTMs and multi-task learning**Marcel Bollmann, Anders Søgaard*2016 · 19 citations*](https://md.research.elamur.ai/free/en/papers/bollmann-2016-improving-historical-spelling-normalization-bi/)
55. [**Synthetic Data for English Lexical Normalization: How Close Can We Get to Manually Annotated Data?**Kelly Dekker, Rob van der Goot*2020 · 18 citations*](https://md.research.elamur.ai/free/en/papers/dekker-2020-synthetic-data-english-lexical-normalization/)
56. [**Antecedent Selection for Sluicing: Structure and Content**Pranav Anand, Daniel Hardt*2016 · 17 citations*](https://md.research.elamur.ai/free/en/papers/anand-2016-antecedent-selection-sluicing-structure-content/)
57. [**Rewarding Coreference Resolvers for Being Consistent with World Knowledge**Rahul Aralikatte, Heather Lent, Ana Valeria Gonzalez, et al.*2019 · 16 citations*](https://md.research.elamur.ai/free/en/papers/aralikatte-2019-rewarding-coreference-resolvers-being-consistent/)
58. [**Bridging Cultural Nuances in Dialogue Agents through Cultural Value Surveys**Yong Cao, Min Chen, Daniel Hershcovich*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/cao-2024-bridging-cultural-nuances-dialogue-agents/)
59. [**Bridging Cultures in the Kitchen: A Framework and Benchmark for Cross-Cultural Recipe Retrieval**Tianyi Hu, Maria Maistro, Daniel Hershcovich*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-bridging-cultures-kitchen-framework-benchmark/)
60. [**"I'll be there for you": The One with Understanding Indirect Answers**Cathrine Damgaard, Paulina Toborek, Trine Eriksen, et al.*2021 · 13 citations*](https://md.research.elamur.ai/free/en/papers/damgaard-2021-i-ll-be-there-you/)
61. [**Multilingual Gradient Word-Order Typology from Universal Dependencies**Emi Baylor, Esther Ploeger, Johannes Bjerva*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/baylor-2024-multilingual-gradient-word-order-typology/)
62. [**Generation of VP Ellipsis: A Corpus-Based Approach**Daniel Hardt, Owen Rambow*2001 · 12 citations*](https://md.research.elamur.ai/free/en/papers/hardt-2001-generation-vp-ellipsis-corpus-based/)
63. [**What can we learn from Semantic Tagging?**Mostafa Abdou, Artur Kulmizev, Vinit Ravishankar, et al.*2018 · 11 citations*](https://md.research.elamur.ai/free/en/papers/abdou-2018-what-can-we-learn-semantic/)
64. [**Historical Text Normalization with Delayed Rewards**Simon Flachs, Marcel Bollmann, Anders Søgaard*2019 · 10 citations*](https://md.research.elamur.ai/free/en/papers/flachs-2019-historical-text-normalization-delayed-rewards/)
65. [**Disambiguating Explicit Discourse Connectives without Oracles**Anders Johannsen, Anders Søgaard*2013 · 10 citations*](https://md.research.elamur.ai/free/en/papers/johannsen-2013-disambiguating-explicit-discourse-connectives-without/)
66. [**Comparison by Conversion: Reverse-Engineering UCCA from Syntax and Lexical Semantics**Daniel Hershcovich, Nathan Schneider, Dotan Dvir, et al.*2020 · 9 citations*](https://md.research.elamur.ai/free/en/papers/hershcovich-2020-comparison-conversion-reverse-engineering-ucca/)
67. [**Negation scope and spelling variation for text-mining of Danish electronic patient records**Cecilia Engel Thomas, Peter Bjødstrup Jensen, Thomas Werge, et al.*2014 · 9 citations*](https://md.research.elamur.ai/free/en/papers/thomas-2014-negation-scope-spelling-variation-text/)
68. [**Model-based Annotation of Coreference**Rahul Aralikatte, Anders Søgaard*2020 · 8 citations*](https://md.research.elamur.ai/free/en/papers/aralikatte-2020-model-based-annotation-coreference/)
69. [**Cross-lingual Semantic Representation for NLP with UCCA**Omri Abend, Dotan Dvir, Daniel Hershcovich, et al.*2020 · 6 citations*](https://md.research.elamur.ai/free/en/papers/abend-2020-cross-lingual-semantic-representation-nlp/)
70. [**A Transformer-based parser for Syriac morphology**Martijn Naaijer, Constantijn Sikkel, Mathias Coeckelbergs, et al.*2023 · 5 citations*](https://md.research.elamur.ai/free/en/papers/naaijer-2023-transformer-based-parser-syriac-morphology/)
71. [**A guide to the dataset explosion in QA, NLI, and commonsense reasoning**Anna Rogers, Anna Rumshisky*2020 · 4 citations*](https://md.research.elamur.ai/free/en/papers/rogers-2020-guide-dataset-explosion-qa-nli/)
72. [**An Empirical Study of Differences between Conversion Schemes and Annotation Guidelines**Anders Søgaard*2013 · 3 citations*](https://md.research.elamur.ai/free/en/papers/sogaard-2013-empirical-study-differences-between-conversion/)
73. [**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/)
74. [**The Transfer of Finite Verb Forms in a Machine Translation System**Bente Maegaard*1982 · 2 citations*](https://md.research.elamur.ai/free/en/papers/maegaard-1982-transfer-finite-verb-forms-machine/)
75. [**Automatically Selecting the Best Dependency Annotation Design with Dynamic Oracles**Guillaume Wisniewski, Ophélie Lacroix, François Yvon*2018 · 2 citations*](https://md.research.elamur.ai/free/en/papers/wisniewski-2018-automatically-selecting-best-dependency-annotation/)
76. [**Language Models for the Restoration of Latin Legal Manuscripts**Shibingfeng Zhang, Edoardo Caraffa, Annafelicia Zuffrano, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/zhang-2026-language-models-restoration-latin-legal/)
77. [**Contribution of Linguistic Typology to Universal Dependency Parsing: An Empirical Investigation**Ali Basirat, Navid Baradaran Hemmati*2024*](https://md.research.elamur.ai/free/en/papers/basirat-2024-contribution-linguistic-typology-universal-dependency/)
78. [**Participant-Reference Shifts in Zech. 1:1-6. An Assessment of Diachronic and Synchronic Approaches**Christian Højgaard Jensen*2016*](https://md.research.elamur.ai/free/en/papers/jensen-2016-participant-reference-shifts-zech-1/)
79. [**Unpacking Ambiguous Structure: A Dataset for Ambiguous Implicit Discourse Relations for English and Egyptian Arabic**Ahmed Ruby, Sara Stymne, Christian Hardmeier*2023*](https://md.research.elamur.ai/free/en/papers/ruby-2023-unpacking-ambiguous-structure-dataset-ambiguous/)
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