---
title: "Who cites Michael I. Jordan"
description: "2,182 papers of the Elamur Research library cite the works of Michael I. Jordan, found in their bibliographies · page 1 of 2 · 1–100; the most cited first."
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---
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# Who cites Michael I. Jordan

2,256 citations of their works from 2,182 papers of our library (of the 140,884 whose bibliographies we read) · 107 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Michael I. Jordan](https://md.research.elamur.ai/free/en/authors/michael-i-jordan/)

**1** [2](https://md.research.elamur.ai/free/en/authors/michael-i-jordan/cited-by/page/2/) [next →](https://md.research.elamur.ai/free/en/authors/michael-i-jordan/cited-by/page/2/)

1. [**Learning Transferable Visual Models From Natural Language Supervision**Alec Radford, Jong Wook Kim, Chris Hallacy, et al.*2021 · 8,295 citations*](https://md.research.elamur.ai/free/en/papers/radford-2021-learning-transferable-visual-models-natural/)
2. [**Learning Word Vectors for Sentiment Analysis**Andrew L. Maas, Raymond E. Daly, Peter T. Pham, et al.*2011 · 4,272 citations*](https://md.research.elamur.ai/free/en/papers/maas-2011-learning-word-vectors-sentiment-analysis/)
3. [**Dynamic Topic Models**David M. Blei, John D. Lafferty*2006 · 2,508 citations*](https://md.research.elamur.ai/free/en/papers/blei-2006-dynamic-topic-models/)
4. [**Word Representations: A Simple and General Method for Semi-Supervised Learning**Joseph Turian, Lev-Arie Ratinov, Yoshua Bengio*2010 · 2,421 citations*](https://md.research.elamur.ai/free/en/papers/turian-2010-word-representations-simple-general-method/)
5. [**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/)
6. [**Reading Tea Leaves: How Humans Interpret Topic Models**Jonathan Chang, Jordan Boyd-Graber, Sean Gerrish, et al.*2009 · 2,037 citations*](https://md.research.elamur.ai/free/en/papers/chang-2009-reading-tea-leaves-humans-interpret-topic/)
7. [**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/)
8. [**Domain Adaptation with Structural Correspondence Learning**John Blitzer, Ryan McDonald, Fernando Pereira*2006 · 1,792 citations*](https://md.research.elamur.ai/free/en/papers/blitzer-2006-domain-adaptation-structural-correspondence-learning/)
9. [**BERTopic: Neural topic modeling with a class-based TF-IDF procedure**Maarten Grootendorst*2022 · 1,729 citations*](https://md.research.elamur.ai/free/en/papers/grootendorst-2022-bertopic-neural-topic-modeling-class/)
10. [**Don't count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors**Marco Baroni, Georgiana Dinu, Germán Kruszewski*2014 · 1,678 citations*](https://md.research.elamur.ai/free/en/papers/baroni-2014-don-t-count-predict-systematic/)
11. [**Named Entity Recognition in Tweets: An Experimental Study**Alan Ritter, Sam Clark, Mausam, et al.*2011 · 1,451 citations*](https://md.research.elamur.ai/free/en/papers/ritter-2011-named-entity-recognition-tweets-experimental/)
12. [**Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions**Richard Socher, Jeffrey Pennington, Eric H. Huang, et al.*2011 · 1,411 citations*](https://md.research.elamur.ai/free/en/papers/socher-2011-semi-supervised-recursive-autoencoders-predicting/)
13. [**Learning Sentiment-Specific Word Embedding for Twitter Sentiment Classification**Duyu Tang, Furu Wei, Nan Yang, et al.*2014 · 1,341 citations*](https://md.research.elamur.ai/free/en/papers/tang-2014-learning-sentiment-specific-word-embedding/)
14. [**Optimizing Semantic Coherence in Topic Models**David Mimno, Hanna Wallach, Edmund Talley, et al.*2011 · 1,334 citations*](https://md.research.elamur.ai/free/en/papers/mimno-2011-optimizing-semantic-coherence-topic-models/)
15. [**The NarrativeQA Reading Comprehension Challenge**Tomáš Kočiský, Jonathan Schwarz, Phil Blunsom, et al.*2018 · 1,026 citations*](https://md.research.elamur.ai/free/en/papers/kocisky-2018-narrativeqa-reading-comprehension-challenge/)
16. [**Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational Autoencoders**Tiancheng Zhao, Ran Zhao, Maxine Eskenazi*2017 · 986 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2017-learning-discourse-level-diversity-neural/)
17. [**Challenges in Data-to-Document Generation**Sam Wiseman, Stuart M. Shieber, Alexander M. Rush*2017 · 846 citations*](https://md.research.elamur.ai/free/en/papers/wiseman-2017-challenges-data-document-generation/)
18. [**Automatic Evaluation of Topic Coherence**David Newman, Jey Han Lau, Karl Grieser, et al.*2010 · 823 citations*](https://md.research.elamur.ai/free/en/papers/newman-2010-automatic-evaluation-topic-coherence/)
19. [**A Joint Model of Text and Aspect Ratings for Sentiment Summarization**Ivan Titov, Ryan McDonald*2008 · 729 citations*](https://md.research.elamur.ai/free/en/papers/titov-2008-joint-model-text-aspect-ratings/)
20. [**Transfer Learning in Natural Language Processing**Sebastian Ruder, Matthew E. Peters, Swabha Swayamdipta, et al.*2019 · 700 citations*](https://md.research.elamur.ai/free/en/papers/ruder-2019-transfer-learning-natural-language-processing/)
21. [**Machine Reading Tea Leaves: Automatically Evaluating Topic Coherence and Topic Model Quality**Jey Han Lau, David Newman, Timothy Baldwin*2014 · 699 citations*](https://md.research.elamur.ai/free/en/papers/lau-2014-machine-reading-tea-leaves-automatically/)
22. [**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/)
23. [**Fast and Robust Neural Network Joint Models for Statistical Machine Translation**Jacob Devlin, Rabih Zbib, Zhongqiang Huang, et al.*2014 · 666 citations*](https://md.research.elamur.ai/free/en/papers/devlin-2014-fast-robust-neural-network-joint/)
24. [**HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models**Junyi Li, Xiaoxue Cheng, Wayne Xin Zhao, et al.*2023 · 646 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-halueval-large-scale-hallucination-evaluation/)
25. [**Exploring Content Models for Multi-Document Summarization**Aria Haghighi, Lucy Vanderwende*2009 · 630 citations*](https://md.research.elamur.ai/free/en/papers/haghighi-2009-exploring-content-models-multi-document/)
26. [**Argument Mining: A Survey**John Lawrence, Chris Reed*2019 · 601 citations*](https://md.research.elamur.ai/free/en/papers/lawrence-2019-argument-mining-survey/)
27. [**Text Embeddings by Weakly-Supervised Contrastive Pre-training**Liang Wang, Nan Yang, Xiaolong Huang, et al.*2022 · 594 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-text-embeddings-weakly-supervised-contrastive/)
28. [**Weakly Supervised Learning of Semantic Parsers for Mapping Instructions to Actions**Yoav Artzi, Luke Zettlemoyer*2013 · 592 citations*](https://md.research.elamur.ai/free/en/papers/artzi-2013-weakly-supervised-learning-semantic-parsers/)
29. [**Automatic Keyphrase Extraction: A Survey of the State of the Art**Kazi Saidul Hasan, Vincent Ng*2014 · 589 citations*](https://md.research.elamur.ai/free/en/papers/hasan-2014-automatic-keyphrase-extraction-survey-state/)
30. [**A Hierarchical Bayesian Language Model Based On Pitman-Yor Processes**Yee Whye Teh*2006 · 571 citations*](https://md.research.elamur.ai/free/en/papers/teh-2006-hierarchical-bayesian-language-model-based/)
31. [**An Unsupervised Aspect-Sentiment Model for Online Reviews**Samuel Brody, Noemie Elhadad*2010 · 569 citations*](https://md.research.elamur.ai/free/en/papers/brody-2010-unsupervised-aspect-sentiment-model-online/)
32. [**Unsupervised Modeling of Twitter Conversations**Alan Ritter, Colin Cherry, Bill Dolan*2010 · 557 citations*](https://md.research.elamur.ai/free/en/papers/ritter-2010-unsupervised-modeling-twitter-conversations/)
33. [**From Frequency to Meaning: Vector Space Models of Semantics**Peter D. Turney, Patrick Pantel*2010 · 554 citations*](https://md.research.elamur.ai/free/en/papers/turney-2010-frequency-meaning-vector-space-models/)
34. [**Creating Training Corpora for NLG Micro-Planners**Claire Gardent, Anastasia Shimorina, Shashi Narayan, et al.*2017 · 526 citations*](https://md.research.elamur.ai/free/en/papers/gardent-2017-creating-training-corpora-nlg-micro/)
35. [**Learning to Solve Arithmetic Word Problems with Verb Categorization**Mohammad Javad Hosseini, Hannaneh Hajishirzi, Oren Etzioni, et al.*2014 · 513 citations*](https://md.research.elamur.ai/free/en/papers/hosseini-2014-learning-solve-arithmetic-word-problems/)
36. [**Semantic Parsing for Single-Relation Question Answering**Wen-tau Yih, Xiaodong He, Christopher Meek*2014 · 483 citations*](https://md.research.elamur.ai/free/en/papers/yih-2014-semantic-parsing-single-relation-question/)
37. [**ToTTo: A Controlled Table-To-Text Generation Dataset**Ankur Parikh, Xuezhi Wang, Sebastian Gehrmann, et al.*2020 · 479 citations*](https://md.research.elamur.ai/free/en/papers/parikh-2020-totto-controlled-table-text-generation/)
38. [**Learning to Generate Reviews and Discovering Sentiment**Alec Radford, Rafal Jozefowicz, Ilya Sutskever*2017 · 467 citations*](https://md.research.elamur.ai/free/en/papers/radford-2017-learning-generate-reviews-discovering-sentiment/)
39. [**Representation Learning Using Multi-Task Deep Neural Networks for Semantic Classification and Information Retrieval**Xiaodong Liu, Jianfeng Gao, Xiaodong He, et al.*2015 · 463 citations*](https://md.research.elamur.ai/free/en/papers/liu-2015-representation-learning-multi-task-deep/)
40. [**Bilingual Word Representations with Monolingual Quality in Mind**Thang Luong, Hieu Pham, Christopher D. Manning*2015 · 453 citations*](https://md.research.elamur.ai/free/en/papers/luong-2015-bilingual-word-representations-monolingual-quality/)
41. [**Temporal Analysis of Language through Neural Language Models**Yoon Kim, Yi-I Chiu, Kentaro Hanaki, et al.*2014 · 439 citations*](https://md.research.elamur.ai/free/en/papers/kim-2014-temporal-analysis-language-through-neural/)
42. [**Experience Grounds Language**Yonatan Bisk, Ari Holtzman, Jesse Thomason, et al.*2020 · 429 citations*](https://md.research.elamur.ai/free/en/papers/bisk-2020-experience-grounds-language/)
43. [**Learning from Bullying Traces in Social Media**Jun-Ming Xu, Kwang-Sung Jun, Xiaojin Zhu, et al.*2012 · 381 citations*](https://md.research.elamur.ai/free/en/papers/xu-2012-learning-bullying-traces-social-media/)
44. [**Multilingual Models for Compositional Distributed Semantics**Karl Moritz Hermann, Phil Blunsom*2014 · 375 citations*](https://md.research.elamur.ai/free/en/papers/hermann-2014-multilingual-models-compositional-distributed-semantics/)
45. [**TopicRank: Graph-Based Topic Ranking for Keyphrase Extraction**Adrien Bougouin, Florian Boudin, Béatrice Daille*2013 · 374 citations*](https://md.research.elamur.ai/free/en/papers/bougouin-2013-topicrank-graph-based-topic-ranking/)
46. [**Pre-training is a Hot Topic: Contextualized Document Embeddings Improve Topic Coherence**Federico Bianchi, Silvia Terragni, Dirk Hovy*2021 · 365 citations*](https://md.research.elamur.ai/free/en/papers/bianchi-2021-pre-training-is-hot-topic/)
47. [**What to talk about and how? Selective Generation using LSTMs with Coarse-to-Fine Alignment**Hongyuan Mei, Mohit Bansal, Matthew R. Walter*2016 · 349 citations*](https://md.research.elamur.ai/free/en/papers/mei-2016-what-talk-about-how-selective/)
48. [**Unsupervised Domain Clusters in Pretrained Language Models**Roee Aharoni, Yoav Goldberg*2020 · 326 citations*](https://md.research.elamur.ai/free/en/papers/aharoni-2020-unsupervised-domain-clusters-pretrained-language/)
49. [**Compressive Transformers for Long-Range Sequence Modelling**Jack W. Rae, Anna Potapenko, Siddhant M. Jayakumar, et al.*2019 · 320 citations*](https://md.research.elamur.ai/free/en/papers/rae-2019-compressive-transformers-long-range-sequence/)
50. [**Globally Coherent Text Generation with Neural Checklist Models**Chloé Kiddon, Luke Zettlemoyer, Yejin Choi*2016 · 301 citations*](https://md.research.elamur.ai/free/en/papers/kiddon-2016-globally-coherent-text-generation-neural/)
51. [**Expert, Crowdsourced, and Machine Assessment of Suicide Risk via Online Postings**Han-Chin Shing, Suraj Nair, Ayah Zirikly, et al.*2018 · 288 citations*](https://md.research.elamur.ai/free/en/papers/shing-2018-expert-crowdsourced-machine-assessment-suicide/)
52. [**A Bayesian Mixed Effects Model of Literary Character**David Bamman, Ted Underwood, Noah A. Smith*2014 · 285 citations*](https://md.research.elamur.ai/free/en/papers/bamman-2014-bayesian-mixed-effects-model-literary/)
53. [**Text Generation from Knowledge Graphs with Graph Transformers**Rik Koncel-Kedziorski, Dhanush Bekal, Yi Luan, et al.*2019 · 284 citations*](https://md.research.elamur.ai/free/en/papers/kedziorski-2019-text-generation-knowledge-graphs-graph/)
54. [**Lexical Generalization in CCG Grammar Induction for Semantic Parsing**Tom Kwiatkowski, Luke Zettlemoyer, Sharon Goldwater, et al.*2011 · 283 citations*](https://md.research.elamur.ai/free/en/papers/kwiatkowski-2011-lexical-generalization-ccg-grammar-induction/)
55. [**Learning Neural Templates for Text Generation**Sam Wiseman, Stuart Shieber, Alexander Rush*2018 · 279 citations*](https://md.research.elamur.ai/free/en/papers/wiseman-2018-learning-neural-templates-text-generation/)
56. [**Automatic Language Identification in Texts: A Survey**Tommi Jauhiainen, Marco Lui, Marcos Zampieri, et al.*2019 · 277 citations*](https://md.research.elamur.ai/free/en/papers/jauhiainen-2019-automatic-language-identification-texts/)
57. [**Learning Discriminative Projections for Text Similarity Measures**Wen-tau Yih, Kristina Toutanova, John C. Platt, et al.*2011 · 273 citations*](https://md.research.elamur.ai/free/en/papers/yih-2011-learning-discriminative-projections-text-similarity/)
58. [**An Explanation of In-context Learning as Implicit Bayesian Inference**Sang Michael Xie, Aditi Raghunathan, Percy Liang, et al.*2021 · 268 citations*](https://md.research.elamur.ai/free/en/papers/xie-2021-explanation-context-learning-implicit-bayesian/)
59. [**Handling Divergent Reference Texts when Evaluating Table-to-Text Generation**Bhuwan Dhingra, Manaal Faruqui, Ankur Parikh, et al.*2019 · 266 citations*](https://md.research.elamur.ai/free/en/papers/dhingra-2019-handling-divergent-reference-texts-when/)
60. [**A Simple Domain-Independent Probabilistic Approach to Generation**Gabor Angeli, Percy Liang, Dan Klein*2010 · 260 citations*](https://md.research.elamur.ai/free/en/papers/angeli-2010-simple-domain-independent-probabilistic-approach/)
61. [**CLPsych 2019 Shared Task: Predicting the Degree of Suicide Risk in Reddit Posts**Ayah Zirikly, Philip Resnik, Özlem Uzuner, et al.*2019 · 246 citations*](https://md.research.elamur.ai/free/en/papers/zirikly-2019-clpsych-2019-shared-task-predicting/)
62. [**Argumentation Mining in User-Generated Web Discourse**Ivan Habernal, Iryna Gurevych*2017 · 243 citations*](https://md.research.elamur.ai/free/en/papers/habernal-2017-argumentation-mining-user-generated-web/)
63. [**A review of sentiment analysis research in Arabic language**Oumaima Oueslati; Erik Cambria; Moez Ben HajHmida;, Habib Ounelli*2020 · 241 citations*](https://md.research.elamur.ai/free/en/papers/oueslati-2020-review-sentiment-analysis-research-arabic/)
64. [**Bayesian Word Sense Induction**Samuel Brody, Mirella Lapata*2009 · 234 citations*](https://md.research.elamur.ai/free/en/papers/brody-2009-bayesian-word-sense-induction/)
65. [**Unsupervised Event Coreference Resolution with Rich Linguistic Features**Cosmin Bejan, Sanda Harabagiu*2010 · 233 citations*](https://md.research.elamur.ai/free/en/papers/bejan-2010-unsupervised-event-coreference-resolution-rich/)
66. [**Unsupervised Models for Coreference Resolution**Vincent Ng*2008 · 223 citations*](https://md.research.elamur.ai/free/en/papers/ng-2008-unsupervised-models-coreference-resolution/)
67. [**Real-Time Open-Domain Question Answering with Dense-Sparse Phrase Index**Minjoon Seo, Jinhyuk Lee, Tom Kwiatkowski, et al.*2019 · 216 citations*](https://md.research.elamur.ai/free/en/papers/seo-2019-real-time-open-domain-question/)
68. [**Logical Natural Language Generation from Open-Domain Tables**Wenhu Chen, Jianshu Chen, Yu Su, et al.*2020 · 209 citations*](https://md.research.elamur.ai/free/en/papers/chen-2020-logical-natural-language-generation-open/)
69. [**Toxicity Detection: Does Context Really Matter?**John Pavlopoulos, Jeffrey Sorensen, Lucas Dixon, et al.*2020 · 198 citations*](https://md.research.elamur.ai/free/en/papers/pavlopoulos-2020-toxicity-detection-does-context-really/)
70. [**Outta Control: Laws of Semantic Change and Inherent Biases in Word Representation Models**Haim Dubossarsky, Daphna Weinshall, Eitan Grossman*2017 · 196 citations*](https://md.research.elamur.ai/free/en/papers/dubossarsky-2017-outta-control-laws-semantic-change/)
71. [**Word Sense Induction for Novel Sense Detection**Jey Han Lau, Paul Cook, Diana McCarthy, et al.*2012 · 187 citations*](https://md.research.elamur.ai/free/en/papers/lau-2012-word-sense-induction-novel-sense/)
72. [**OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents**Hugo Laurençon, Lucile Saulnier, Leo Tronchon, et al.*2023 · 183 citations*](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2023-obelics-open-web-scale-filtered/)
73. [**Unsupervised Coreference Resolution in a Nonparametric Bayesian Model**Aria Haghighi, Dan Klein*2007 · 182 citations*](https://md.research.elamur.ai/free/en/papers/haghighi-2007-unsupervised-coreference-resolution-nonparametric-bayesian/)
74. [**MediaSum: A Large-scale Media Interview Dataset for Dialogue Summarization**Chenguang Zhu, Yang Liu, Jie Mei, et al.*2021 · 176 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2021-mediasum-large-scale-media-interview/)
75. [**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/)
76. [**Automatic Detection and Language Identification of Multilingual Documents**Marco Lui, Jey Han Lau, Timothy Baldwin*2014 · 157 citations*](https://md.research.elamur.ai/free/en/papers/lui-2014-automatic-detection-language-identification-multilingual/)
77. [**DART: Open-Domain Structured Data Record to Text Generation**Linyong Nan, Dragomir Radev, Rui Zhang, et al.*2020 · 154 citations*](https://md.research.elamur.ai/free/en/papers/nan-2020-dart-open-domain-structured-data/)
78. [**Neural Net Models of Open-domain Discourse Coherence**Jiwei Li, Dan Jurafsky*2017 · 147 citations*](https://md.research.elamur.ai/free/en/papers/li-2017-neural-net-models-open-domain/)
79. [**A Retrospective Analysis of the Fake News Challenge Stance-Detection Task**Andreas Hanselowski, Avinesh PVS, Benjamin Schiller, et al.*2018 · 132 citations*](https://md.research.elamur.ai/free/en/papers/hanselowski-2018-retrospective-analysis-fake-news-challenge/)
80. [**Machine Learning for Ancient Languages: A Survey**Thea Sommerschield, Yannis Assael, John Pavlopoulos, et al.*2023 · 123 citations*](https://md.research.elamur.ai/free/en/papers/sommerschield-2023-machine-learning-ancient-languages-survey/)
81. [**Findings of the WMT 2019 Shared Task on Automatic Post-Editing**Rajen Chatterjee, Christian Federmann, Matteo Negri, et al.*2019 · 102 citations*](https://md.research.elamur.ai/free/en/papers/chatterjee-2019-findings-wmt-2019-shared-task/)
82. [**Learning Latent Personas of Film Characters**David Bamman, Brendan O'Connor, Noah A. Smith*2013 · 101 citations*](https://md.research.elamur.ai/free/en/papers/bamman-2013-learning-latent-personas-film-characters/)
83. [**Unsupervised Event Coreference Resolution**Cosmin Adrian Bejan, Sanda Harabagiu*2014 · 83 citations*](https://md.research.elamur.ai/free/en/papers/bejan-2014-unsupervised-event-coreference-resolution/)
84. [**A Context-Theoretic Framework for Compositionality in Distributional Semantics**Daoud Clarke*2012 · 83 citations*](https://md.research.elamur.ai/free/en/papers/clarke-2012-context-theoretic-framework-compositionality-distributional/)
85. [**Streaming Cross Document Entity Coreference Resolution**Delip Rao, Paul McNamee, Mark Dredze*2010 · 67 citations*](https://md.research.elamur.ai/free/en/papers/rao-2010-streaming-cross-document-entity-coreference/)
86. [**Idiom Token Classification using Sentential Distributed Semantics**Giancarlo Salton, Robert Ross, John Kelleher*2016 · 65 citations*](https://md.research.elamur.ai/free/en/papers/salton-2016-idiom-token-classification-sentential-distributed/)
87. [**A Linguistic Resource for Discovering Event Structures and Resolving Event Coreference**Cosmin Bejan, Sanda Harabagiu*2008 · 64 citations*](https://md.research.elamur.ai/free/en/papers/bejan-2008-linguistic-resource-discovering-event-structures/)
88. [**Evaluating Topic Coherence Using Distributional Semantics**Nikolaos Aletras, Mark Stevenson*2013 · 63 citations*](https://md.research.elamur.ai/free/en/papers/aletras-2013-evaluating-topic-coherence-distributional-semantics/)
89. [**A Discriminative Hierarchical Model for Fast Coreference at Large Scale**Michael Wick, Sameer Singh, Andrew McCallum*2012 · 57 citations*](https://md.research.elamur.ai/free/en/papers/wick-2012-discriminative-hierarchical-model-fast-coreference/)
90. [**Multilingual Stance Detection in Tweets: The Catalonia Independence Corpus**Elena Zotova, Rodrigo Agerri, Manuel Nuñez, et al.*2020 · 46 citations*](https://md.research.elamur.ai/free/en/papers/zotova-2020-multilingual-stance-detection-tweets-catalonia/)
91. [**Detecting Suicidality in Arabic Tweets Using Machine Learning and Deep Learning Techniques**Asma Abdulsalam, Areej Alhothali, Saleh Al-Ghamdi*2023 · 29 citations*](https://md.research.elamur.ai/free/en/papers/abdulsalam-2023-detecting-suicidality-arabic-tweets-using/)
92. [**Underspecified Universal Dependency Structures as Inputs for Multilingual Surface Realisation**Simon Mille, Anja Belz, Bernd Bohnet, et al.*2018 · 26 citations*](https://md.research.elamur.ai/free/en/papers/mille-2018-underspecified-universal-dependency-structures-as/)
93. [**A Probabilistic Annotation Model for Crowdsourcing Coreference**Silviu Paun, Jon Chamberlain, Udo Kruschwitz, et al.*2018 · 25 citations*](https://md.research.elamur.ai/free/en/papers/paun-2018-probabilistic-annotation-model-crowdsourcing-coreference/)
94. [**Speaker-change Aware CRF for Dialogue Act Classification**Guokan Shang, Antoine Tixier, Michalis Vazirgiannis, et al.*2020 · 23 citations*](https://md.research.elamur.ai/free/en/papers/shang-2020-speaker-change-aware-crf-dialogue/)
95. [**A Multi-Task Dataset for Assessing Discourse Coherence in Chinese Essays: Structure, Theme, and Logic Analysis**Hongyi Wu, Xinshu Shen, Man Lan, et al.*2023 · 12 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-multi-task-dataset-assessing-discourse/)
96. [**Hebrew Psychological Lexicons**Natalie Shapira, Dana Atzil-Slonim, Daniel Juravski, et al.*2021 · 9 citations*](https://md.research.elamur.ai/free/en/papers/shapira-2021-hebrew-psychological-lexicons/)
97. [**Are idioms surprising?**J. Nathanael Philipp, Michael Richter, Erik Daas, et al.*2023 · 3 citations*](https://md.research.elamur.ai/free/en/papers/philipp-2023-are-idioms-surprising/)
98. [**Morphology-rich Alphasyllabary Embeddings**Amanuel Mersha, Stephen Wu*2020 · 2 citations*](https://md.research.elamur.ai/free/en/papers/mersha-2020-morphology-rich-alphasyllabary-embeddings/)
99. [**Evaluating Machine Translation Datasets for Low-Web Data Languages: A Gendered Lens**Hellina Hailu Nigatu, Bethelhem Yemane Mamo, Bontu Fufa Balcha, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/nigatu-2026-evaluating-machine-translation-datasets-low/)
100. [**Graph convolutional networks for exploring authorship hypotheses**Tom Lippincott*2019 · 1 citation*](https://md.research.elamur.ai/free/en/papers/lippincott-2019-graph-convolutional-networks-exploring-authorship/)

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