---
title: "Who cites Efficient Estimation of Word Representations in…"
description: "3,846 papers of the Elamur Research library cite «Efficient Estimation of Word Representations in Vector Space», found in their bibliographies · page 2 of…"
canonical: "https://research.elamur.ai/free/en/papers/mikolov-2013-efficient-estimation-word-representations-vector/cited-by/page/2/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/mikolov-2013-efficient-estimation-word-representations-vector/cited-by/page/2/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Efficient Estimation of Word Representations in…](https://md.research.elamur.ai/free/en/papers/mikolov-2013-efficient-estimation-word-representations-vector/) / [cited by](https://md.research.elamur.ai/free/en/papers/mikolov-2013-efficient-estimation-word-representations-vector/cited-by/) / page 2

# Who cites «Efficient Estimation of Word Representations in Vector Space»

3,846 papers of our library cite it (of the 140,884 whose bibliographies we read) · 285 with a page here, the most cited first · page 2 of 3 · 101–200 · [← the paper](https://md.research.elamur.ai/free/en/papers/mikolov-2013-efficient-estimation-word-representations-vector/)

[← prev](https://md.research.elamur.ai/free/en/papers/mikolov-2013-efficient-estimation-word-representations-vector/cited-by/) [1](https://md.research.elamur.ai/free/en/papers/mikolov-2013-efficient-estimation-word-representations-vector/cited-by/) **2** [3](https://md.research.elamur.ai/free/en/papers/mikolov-2013-efficient-estimation-word-representations-vector/cited-by/page/3/) [next →](https://md.research.elamur.ai/free/en/papers/mikolov-2013-efficient-estimation-word-representations-vector/cited-by/page/3/)

101. [**That's So Annoying!!!: A Lexical and Frame-Semantic Embedding Based Data Augmentation Approach to Automatic Categorization of Annoying Behaviors using #petpeeve Tweets**William Yang Wang, Diyi Yang*2015 · 391 citations*](https://md.research.elamur.ai/free/en/papers/wang-2015-that-s-so-annoying-lexical/)
102. [**CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning**Justin Johnson, Bharath Hariharan, Laurens van der Maaten, et al.*2016 · 387 citations*](https://md.research.elamur.ai/free/en/papers/johnson-2016-clevr-diagnostic-dataset-compositional-language/)
103. [**Gender and Representation Bias in GPT-3 Generated Stories**Li Lucy, David Bamman*2021 · 382 citations*](https://md.research.elamur.ai/free/en/papers/lucy-2021-gender-representation-bias-gpt-3/)
104. [**Many Languages, One Parser**Waleed Ammar, George Mulcaire, Miguel Ballesteros, et al.*2016 · 382 citations*](https://md.research.elamur.ai/free/en/papers/ammar-2016-many-languages-one-parser/)
105. [**From Paraphrase Database to Compositional Paraphrase Model and Back**John Wieting, Mohit Bansal, Kevin Gimpel, et al.*2015 · 375 citations*](https://md.research.elamur.ai/free/en/papers/wieting-2015-paraphrase-database-compositional-paraphrase-model/)
106. [**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/)
107. [**WASSA-2017 Shared Task on Emotion Intensity**Saif Mohammad, Felipe Bravo-Marquez*2017 · 368 citations*](https://md.research.elamur.ai/free/en/papers/mohammad-2017-wassa-2017-shared-task-emotion/)
108. [**Political Ideology Detection Using Recursive Neural Networks**Mohit Iyyer, Peter Enns, Jordan Boyd-Graber, et al.*2014 · 368 citations*](https://md.research.elamur.ai/free/en/papers/iyyer-2014-political-ideology-detection-recursive-neural/)
109. [**A Latent Variable Model Approach to PMI-based Word Embeddings**Sanjeev Arora, Yuanzhi Li, Yingyu Liang, et al.*2016 · 365 citations*](https://md.research.elamur.ai/free/en/papers/arora-2016-latent-variable-model-approach-pmi/)
110. [**Analyzing the Behavior of Visual Question Answering Models**Aishwarya Agrawal, Dhruv Batra, Devi Parikh*2016 · 358 citations*](https://md.research.elamur.ai/free/en/papers/agrawal-2016-analyzing-behavior-visual-question-answering/)
111. [**A Unified Model for Word Sense Representation and Disambiguation**Xinxiong Chen, Zhiyuan Liu, Maosong Sun*2014 · 358 citations*](https://md.research.elamur.ai/free/en/papers/chen-2014-unified-model-word-sense-representation/)
112. [**Parameter-Efficient Transfer Learning with Diff Pruning**Demi Guo, Alexander Rush, Yoon Kim*2021 · 355 citations*](https://md.research.elamur.ai/free/en/papers/guo-2021-parameter-efficient-transfer-learning-diff/)
113. [**Exploring Neural Text Simplification Models**Sergiu Nisioi, Sanja Štajner, Simone Paolo Ponzetto, et al.*2017 · 353 citations*](https://md.research.elamur.ai/free/en/papers/nisioi-2017-exploring-neural-text-simplification-models/)
114. [**SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection**Dominik Schlechtweg, Barbara McGillivray, Simon Hengchen, et al.*2020 · 351 citations*](https://md.research.elamur.ai/free/en/papers/schlechtweg-2020-semeval-2020-task-1-unsupervised/)
115. [**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/)
116. [**SensEmbed: Learning Sense Embeddings for Word and Relational Similarity**Ignacio Iacobacci, Mohammad Taher Pilehvar, Roberto Navigli*2015 · 348 citations*](https://md.research.elamur.ai/free/en/papers/iacobacci-2015-sensembed-learning-sense-embeddings-word/)
117. [**RobBERT: a Dutch RoBERTa-based Language Model**Pieter Delobelle, Thomas Winters, Bettina Berendt*2020 · 346 citations*](https://md.research.elamur.ai/free/en/papers/delobelle-2020-robbert-dutch-roberta-based-language/)
118. [**Stanford's Graph-based Neural Dependency Parser at the CoNLL 2017 Shared Task**Timothy Dozat, Peng Qi, Christopher D. Manning*2017 · 346 citations*](https://md.research.elamur.ai/free/en/papers/dozat-2017-stanford-s-graph-based-neural/)
119. [**Black is to Criminal as Caucasian is to Police: Detecting and Removing Multiclass Bias in Word Embeddings**Thomas Manzini, Lim Yao Chong, Alan W Black, et al.*2019 · 332 citations*](https://md.research.elamur.ai/free/en/papers/manzini-2019-black-is-criminal-as-caucasian/)
120. [**Problems With Evaluation of Word Embeddings Using Word Similarity Tasks**Manaal Faruqui, Yulia Tsvetkov, Pushpendre Rastogi, et al.*2016 · 332 citations*](https://md.research.elamur.ai/free/en/papers/faruqui-2016-problems-evaluation-word-embeddings-word/)
121. [**A Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural Networks**Soujanya Poria, Erik Cambria, Devamanyu Hazarika, et al.*2016 · 331 citations*](https://md.research.elamur.ai/free/en/papers/poria-2016-deeper-look-into-sarcastic-tweets/)
122. [**Unsupervised Corpus Aware Language Model Pre-training for Dense Passage Retrieval**Luyu Gao, Jamie Callan*2022 · 328 citations*](https://md.research.elamur.ai/free/en/papers/gao-2022-unsupervised-corpus-aware-language-model/)
123. [**Learning Semantic Hierarchies via Word Embeddings**Ruiji Fu, Jiang Guo, Bing Qin, et al.*2014 · 327 citations*](https://md.research.elamur.ai/free/en/papers/fu-2014-learning-semantic-hierarchies-word-embeddings/)
124. [**Do Supervised Distributional Methods Really Learn Lexical Inference Relations?**Omer Levy, Steffen Remus, Chris Biemann, et al.*2015 · 325 citations*](https://md.research.elamur.ai/free/en/papers/levy-2015-do-supervised-distributional-methods-really/)
125. [**Text and Code Embeddings by Contrastive Pre-Training**Arvind Neelakantan, Tao Xu, Raul Puri, et al.*2022 · 316 citations*](https://md.research.elamur.ai/free/en/papers/neelakantan-2022-text-code-embeddings-contrastive-pre/)
126. [**SimVerb-3500: A Large-Scale Evaluation Set of Verb Similarity**Daniela Gerz, Ivan Vulić, Felix Hill, et al.*2016 · 315 citations*](https://md.research.elamur.ai/free/en/papers/gerz-2016-simverb-3500-large-scale-evaluation/)
127. [**Improving Distributional Similarity with Lessons Learned from Word Embeddings**Omer Levy, Yoav Goldberg, Ido Dagan*2015 · 313 citations*](https://md.research.elamur.ai/free/en/papers/levy-2015-improving-distributional-similarity-lessons-learned/)
128. [**A Transformer-based approach to Irony and Sarcasm detection**Rolandos Alexandros Potamias, Georgios Siolas, Andreas - Georgios Stafylopatis*2019 · 312 citations*](https://md.research.elamur.ai/free/en/papers/potamias-2019-transformer-based-approach-irony-sarcasm/)
129. [**Analogy-based detection of morphological and semantic relations with word embeddings: what works and what doesn't.**Anna Gladkova, Aleksandr Drozd, Satoshi Matsuoka*2016 · 311 citations*](https://md.research.elamur.ai/free/en/papers/gladkova-2016-analogy-based-detection-morphological-semantic/)
130. [**Exploiting Argument Information to Improve Event Detection via Supervised Attention Mechanisms**Shulin Liu, Yubo Chen, Kang Liu, et al.*2017 · 309 citations*](https://md.research.elamur.ai/free/en/papers/liu-2017-exploiting-argument-information-improve-event/)
131. [**Show Me Your Evidence - an Automatic Method for Context Dependent Evidence Detection**Ruty Rinott, Lena Dankin, Carlos Alzate Perez, et al.*2015 · 296 citations*](https://md.research.elamur.ai/free/en/papers/rinott-2015-show-me-your-evidence-automatic/)
132. [**Black Holes and White Rabbits: Metaphor Identification with Visual Features**Ekaterina Shutova, Douwe Kiela, Jean Maillard*2016 · 292 citations*](https://md.research.elamur.ai/free/en/papers/shutova-2016-black-holes-white-rabbits-metaphor/)
133. [**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/)
134. [**Emotion Intensities in Tweets**Saif Mohammad, Felipe Bravo-Marquez*2017 · 290 citations*](https://md.research.elamur.ai/free/en/papers/mohammad-2017-emotion-intensities-tweets/)
135. [**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/)
136. [**Diachronic word embeddings and semantic shifts: a survey**Andrey Kutuzov, Lilja Øvrelid, Terrence Szymanski, et al.*2018 · 282 citations*](https://md.research.elamur.ai/free/en/papers/kutuzov-2018-diachronic-word-embeddings-semantic-shifts/)
137. [**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/)
138. [**Zero-Shot Transfer Learning for Event Extraction**Lifu Huang, Heng Ji, Kyunghyun Cho, et al.*2018 · 272 citations*](https://md.research.elamur.ai/free/en/papers/huang-2018-zero-shot-transfer-learning-event/)
139. [**Cross-lingual Dependency Parsing Based on Distributed Representations**Jiang Guo, Wanxiang Che, David Yarowsky, et al.*2015 · 269 citations*](https://md.research.elamur.ai/free/en/papers/guo-2015-cross-lingual-dependency-parsing-based/)
140. [**From Light to Rich ERE: Annotation of Entities, Relations, and Events**Zhiyi Song, Ann Bies, Stephanie Strassel, et al.*2015 · 263 citations*](https://md.research.elamur.ai/free/en/papers/song-2015-light-rich-ere-annotation-entities/)
141. [**Towards Debiasing Sentence Representations**Paul Pu Liang, Irene Mengze Li, Emily Zheng, et al.*2020 · 259 citations*](https://md.research.elamur.ai/free/en/papers/liang-2020-debiasing-sentence-representations/)
142. [**Multilingual is not enough: BERT for Finnish**Antti Virtanen, Jenna Kanerva, Rami Ilo, et al.*2019 · 256 citations*](https://md.research.elamur.ai/free/en/papers/virtanen-2019-multilingual-enough-bert-finnish/)
143. [**BPEmb: Tokenization-free Pre-trained Subword Embeddings in 275 Languages**Benjamin Heinzerling, Michael Strube*2018 · 256 citations*](https://md.research.elamur.ai/free/en/papers/heinzerling-2018-bpemb-tokenization-free-pre-trained/)
144. [**Survey of Low-Resource Machine Translation**Barry Haddow, Rachel Bawden, Antonio Valerio Miceli Barone, et al.*2022 · 251 citations*](https://md.research.elamur.ai/free/en/papers/haddow-2022-survey-low-resource-machine-translation/)
145. [**Generating Datasets with Pretrained Language Models**Timo Schick, Hinrich Schutze*2021 · 250 citations*](https://md.research.elamur.ai/free/en/papers/schick-2021-generating-datasets-pretrained-language-models/)
146. [**BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model**Alex Wang, Kyunghyun Cho*2019 · 249 citations*](https://md.research.elamur.ai/free/en/papers/wang-2019-bert-has-mouth-must-speak/)
147. [**Demographic Factors Improve Classification Performance**Dirk Hovy*2015 · 244 citations*](https://md.research.elamur.ai/free/en/papers/hovy-2015-demographic-factors-improve-classification-performance/)
148. [**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/)
149. [**Classification and Clustering of Arguments with Contextualized Word Embeddings**Nils Reimers, Benjamin Schiller, Tilman Beck, et al.*2019 · 239 citations*](https://md.research.elamur.ai/free/en/papers/reimers-2019-classification-clustering-arguments-contextualized-word/)
150. [**MITRE at SemEval-2016 Task 6: Transfer Learning for Stance Detection**Guido Zarrella, Amy Marsh*2016 · 223 citations*](https://md.research.elamur.ai/free/en/papers/zarrella-2016-mitre-semeval-2016-task-6/)
151. [**Data-Driven Sentence Simplification: Survey and Benchmark**Fernando Alva-Manchego, Carolina Scarton, Lucia Specia*2020 · 213 citations*](https://md.research.elamur.ai/free/en/papers/manchego-2020-data-driven-sentence-simplification-survey/)
152. [**Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP**Timo Schick, Sahana Udupa, Hinrich Schutze*2021 · 207 citations*](https://md.research.elamur.ai/free/en/papers/schick-2021-self-diagnosis-self-debiasing-proposal/)
153. [**Predictive Biases in Natural Language Processing Models: A Conceptual Framework and Overview**Deven Shah, H. Andrew Schwartz, Dirk Hovy*2019 · 201 citations*](https://md.research.elamur.ai/free/en/papers/shah-2019-predictive-biases-natural-language-processing/)
154. [**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/)
155. [**Leveraging FrameNet to Improve Automatic Event Detection**Shulin Liu, Yubo Chen, Shizhu He, et al.*2016 · 163 citations*](https://md.research.elamur.ai/free/en/papers/liu-2016-leveraging-framenet-improve-automatic-event/)
156. [**A Sentiment Analysis Dataset for Code-Mixed Malayalam-English**Bharathi Raja Chakravarthi, Navya Jose, Shardul Suryawanshi, et al.*2020 · 158 citations*](https://md.research.elamur.ai/free/en/papers/chakravarthi-2020-sentiment-analysis-dataset-code-mixed/)
157. [**pkudblab at SemEval-2016 Task 6 : A Specific Convolutional Neural Network System for Effective Stance Detection**Wan Wei, Xiao Zhang, Xuqin Liu, et al.*2016 · 155 citations*](https://md.research.elamur.ai/free/en/papers/wei-2016-pkudblab-semeval-2016-task-6/)
158. [**Lexicon Infused Phrase Embeddings for Named Entity Resolution**Alexandre Passos, Vineet Kumar, Andrew McCallum*2014 · 143 citations*](https://md.research.elamur.ai/free/en/papers/passos-2014-lexicon-infused-phrase-embeddings-named/)
159. [**Sarcastic or Not: Word Embeddings to Predict the Literal or Sarcastic Meaning of Words**Debanjan Ghosh, Weiwei Guo, Smaranda Muresan*2015 · 141 citations*](https://md.research.elamur.ai/free/en/papers/ghosh-2015-sarcastic-or-not-word-embeddings/)
160. [**Affective and Contextual Embedding for Sarcasm Detection**Nastaran Babanejad, Heidar Davoudi, Aijun An, et al.*2020 · 135 citations*](https://md.research.elamur.ai/free/en/papers/babanejad-2020-affective-contextual-embedding-sarcasm-detection/)
161. [**Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches**Shane Storks, Qiaozi Gao, Joyce Y. Chai*2019 · 134 citations*](https://md.research.elamur.ai/free/en/papers/storks-2019-recent-advances-natural-language-inference/)
162. [**Dialogue Act Classification in Domain-Independent Conversations Using a Deep Recurrent Neural Network**Hamed Khanpour, Nishitha Guntakandla, Rodney Nielsen*2016 · 134 citations*](https://md.research.elamur.ai/free/en/papers/khanpour-2016-dialogue-act-classification-domain-independent/)
163. [**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/)
164. [**Still a Pain in the Neck: Evaluating Text Representations on Lexical Composition**Vered Shwartz, Ido Dagan*2019 · 129 citations*](https://md.research.elamur.ai/free/en/papers/shwartz-2019-still-pain-neck-evaluating-text/)
165. [**Annotation, Modelling and Analysis of Fine-Grained Emotions on a Stance and Sentiment Detection Corpus**Hendrik Schuff, Jeremy Barnes, Julian Mohme, et al.*2017 · 129 citations*](https://md.research.elamur.ai/free/en/papers/schuff-2017-annotation-modelling-analysis-fine-grained/)
166. [**Arabic aspect based sentiment analysis using bidirectional GRU based models**Mohammed M.Abdelgwad, Taysir Hassan A Soliman, Ahmed I.Taloba, et al.*2021 · 127 citations*](https://md.research.elamur.ai/free/en/papers/m-abdelgwad-2021-arabic-aspect-based-sentiment-analysis/)
167. [**Sarcasm Analysis Using Conversation Context**Debanjan Ghosh, Alexander R. Fabbri, Smaranda Muresan*2018 · 118 citations*](https://md.research.elamur.ai/free/en/papers/ghosh-2018-sarcasm-analysis-conversation-context/)
168. [**Intrinsic Bias Metrics Do Not Correlate with Application Bias**Seraphina Goldfarb-Tarrant, Rebecca Marchant, Ricardo Muñoz Sánchez, et al.*2021 · 116 citations*](https://md.research.elamur.ai/free/en/papers/tarrant-2021-intrinsic-bias-metrics-do-not/)
169. [**Simple and Effective Text Simplification Using Semantic and Neural Methods**Elior Sulem, Omri Abend, Ari Rappoport*2018 · 113 citations*](https://md.research.elamur.ai/free/en/papers/sulem-2018-simple-effective-text-simplification-semantic/)
170. [**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/)
171. [**Superbizarre Is Not Superb: Derivational Morphology Improves BERT's Interpretation of Complex Words**Valentin, Hofmann*2021 · 101 citations*](https://md.research.elamur.ai/free/en/papers/hofmann-2021-superbizarre-derivational/)
172. [**Don't Throw Those Morphological Analyzers Away Just Yet: Neural Morphological Disambiguation for Arabic**Nasser Zalmout, Nizar Habash*2017 · 96 citations*](https://md.research.elamur.ai/free/en/papers/zalmout-2017-don-t-throw-those-morphological/)
173. [**Arabic Diacritization with Recurrent Neural Networks**Yonatan Belinkov, James Glass*2015 · 93 citations*](https://md.research.elamur.ai/free/en/papers/belinkov-2015-arabic-diacritization-recurrent-neural-networks/)
174. [**Twitter Universal Dependency Parsing for African-American and Mainstream American English**Su Lin Blodgett, Johnny Wei, Brendan O'Connor*2018 · 92 citations*](https://md.research.elamur.ai/free/en/papers/blodgett-2018-twitter-universal-dependency-parsing-african/)
175. [**Skywork: A More Open Bilingual Foundation Model**Tianwen Wei, Liang Zhao, Lichang Zhang, et al.*2023 · 91 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-skywork-more-open-bilingual/)
176. [**AStitchInLanguageModels: Dataset and Methods for the Exploration of Idiomaticity in Pre-Trained Language Models**Harish Tayyar Madabushi, Edward Gow-Smith, Carolina Scarton, et al.*2021 · 86 citations*](https://md.research.elamur.ai/free/en/papers/madabushi-2021-astitchinlanguagemodels-dataset-methods-exploration-idiomaticity/)
177. [**A Neural Network Approach to Selectional Preference Acquisition**Van de Cruys, Tim*2014 · 79 citations*](https://md.research.elamur.ai/free/en/papers/cruys-2014-neural-network-approach-selectional-preference/)
178. [**A Systematic Study of Neural Discourse Models for Implicit Discourse Relation**Attapol Rutherford, Vera Demberg, Nianwen Xue*2017 · 78 citations*](https://md.research.elamur.ai/free/en/papers/rutherford-2017-systematic-study-neural-discourse-models/)
179. [**Wojood: Nested Arabic Named Entity Corpus and Recognition using BERT**Mustafa Jarrar, Mohammed Khalilia, Sana Ghanem*2022 · 73 citations*](https://md.research.elamur.ai/free/en/papers/jarrar-2022-wojood-nested-arabic-named-entity/)
180. [**Is Neural Machine Translation Ready for Deployment? A Case Study on 30 Translation Directions**Marcin Junczys-Dowmunt, Tomasz Dwojak, Hieu Hoang*2016 · 67 citations*](https://md.research.elamur.ai/free/en/papers/dowmunt-2016-is-neural-machine-translation-ready/)
181. [**Evaluating Various Tokenizers for Arabic Text Classification**Zaid Alyafeai, Maged S. Al-shaibani, Mustafa Ghaleb, et al.*2021 · 66 citations*](https://md.research.elamur.ai/free/en/papers/alyafeai-2021-evaluating-various-tokenizers-arabic-text/)
182. [**Multi-Relational Script Learning for Discourse Relations**I-Ta Lee, Dan Goldwasser*2019 · 66 citations*](https://md.research.elamur.ai/free/en/papers/lee-2019-multi-relational-script-learning-discourse/)
183. [**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/)
184. [**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/)
185. [**Evaluating the Evaluation Metrics for Style Transfer: A Case Study in Multilingual Formality Transfer**Eleftheria Briakou, Sweta Agrawal, Joel Tetreault, et al.*2021 · 49 citations*](https://md.research.elamur.ai/free/en/papers/briakou-2021-evaluating-evaluation-metrics-style-transfer/)
186. [**Two End-to-end Shallow Discourse Parsers for English and Chinese in CoNLL-2016 Shared Task**Jianxiang Wang, Man Lan*2016 · 47 citations*](https://md.research.elamur.ai/free/en/papers/wang-2016-two-end-end-shallow-discourse/)
187. [**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/)
188. [**Exploring Compositional Architectures and Word Vector Representations for Prepositional Phrase Attachment**Yonatan Belinkov, Tao Lei, Regina Barzilay, et al.*2014 · 45 citations*](https://md.research.elamur.ai/free/en/papers/belinkov-2014-exploring-compositional-architectures-word-vector/)
189. [**Learning Contextually Informed Representations for Linear-Time Discourse Parsing**Yang Liu, Mirella Lapata*2017 · 44 citations*](https://md.research.elamur.ai/free/en/papers/liu-2017-learning-contextually-informed-representations-linear/)
190. [**Using active learning to expand training data for implicit discourse relation recognition**Yang Xu, Yu Hong, Huibin Ruan, et al.*2018 · 42 citations*](https://md.research.elamur.ai/free/en/papers/xu-2018-active-learning-expand-training-data/)
191. [**Robust Non-Explicit Neural Discourse Parser in English and Chinese**Attapol Rutherford, Nianwen Xue*2016 · 41 citations*](https://md.research.elamur.ai/free/en/papers/rutherford-2016-robust-non-explicit-neural-discourse/)
192. [**A Few Topical Tweets are Enough for Effective User Stance Detection**Younes Samih, Kareem Darwish*2021 · 40 citations*](https://md.research.elamur.ai/free/en/papers/samih-2021-few-topical-tweets-are-enough/)
193. [**Neural Cross-Lingual Coreference Resolution And Its Application To Entity Linking**Gourab Kundu, Avi Sil, Radu Florian, et al.*2018 · 40 citations*](https://md.research.elamur.ai/free/en/papers/kundu-2018-neural-cross-lingual-coreference-resolution/)
194. [**ASAD: A Twitter-based Benchmark Arabic Sentiment Analysis Dataset**Basma Alharbi, Hind Alamro, Manal Alshehri, et al.*2020 · 39 citations*](https://md.research.elamur.ai/free/en/papers/alharbi-2020-asad-twitter-based-benchmark-arabic/)
195. [**Removing the Training Wheels: A Coreference Dataset that Entertains Humans and Challenges Computers**Anupam Guha, Mohit Iyyer, Danny Bouman, et al.*2015 · 39 citations*](https://md.research.elamur.ai/free/en/papers/guha-2015-removing-training-wheels-coreference-dataset/)
196. [**Semeval-2022 Task 1: CODWOE – Comparing Dictionaries and Word Embeddings**Timothee Mickus, Kees Van Deemter, Mathieu Constant, et al.*2022 · 38 citations*](https://md.research.elamur.ai/free/en/papers/mickus-2022-codwoe-dictionaries-embeddings/)
197. [**Habibi - a multi Dialect multi National Arabic Song Lyrics Corpus**Mahmoud El-Haj*2020 · 38 citations*](https://md.research.elamur.ai/free/en/papers/haj-2020-habibi-multi-dialect-multi-national/)
198. [**Empirical evaluation of shallow and deep learning classifiers for Arabic sentiment analysis**Ali Bou Nassif, Abdollah Masoud Darya, Ashraf Elnagar*2021 · 34 citations*](https://md.research.elamur.ai/free/en/papers/nassif-2021-empirical-evaluation-shallow-deep-learning/)
199. [**Bilingually-constrained Synthetic Data for Implicit Discourse Relation Recognition**Changxing Wu, Xiaodong Shi, Yidong Chen, et al.*2016 · 34 citations*](https://md.research.elamur.ai/free/en/papers/wu-2016-bilingually-constrained-synthetic-data-implicit/)
200. [**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/)

[← prev](https://md.research.elamur.ai/free/en/papers/mikolov-2013-efficient-estimation-word-representations-vector/cited-by/) [1](https://md.research.elamur.ai/free/en/papers/mikolov-2013-efficient-estimation-word-representations-vector/cited-by/) **2** [3](https://md.research.elamur.ai/free/en/papers/mikolov-2013-efficient-estimation-word-representations-vector/cited-by/page/3/) [next →](https://md.research.elamur.ai/free/en/papers/mikolov-2013-efficient-estimation-word-representations-vector/cited-by/page/3/)

- [← back to](https://md.research.elamur.ai/free/en/papers/mikolov-2013-efficient-estimation-word-representations-vector/) — Efficient Estimation of Word Representations in Vector Space