---
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 3 of…"
canonical: "https://research.elamur.ai/free/en/papers/mikolov-2013-efficient-estimation-word-representations-vector/cited-by/page/3/"
---
[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/3/)

[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 3

# 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 3 of 3 · 201–285 · [← 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/page/2/) [1](https://md.research.elamur.ai/free/en/papers/mikolov-2013-efficient-estimation-word-representations-vector/cited-by/) [2](https://md.research.elamur.ai/free/en/papers/mikolov-2013-efficient-estimation-word-representations-vector/cited-by/page/2/) **3**

201. [**SherLIiC: A Typed Event-Focused Lexical Inference Benchmark for Evaluating Natural Language Inference**Martin Schmitt, Hinrich Schütze*2019 · 28 citations*](https://md.research.elamur.ai/free/en/papers/schmitt-2019-sherliic-typed-event-focused-lexical/)
202. [**Speech Act Modeling of Written Asynchronous Conversations with Task-Specific Embeddings and Conditional Structured Models**Shafiq Joty, Enamul Hoque*2016 · 27 citations*](https://md.research.elamur.ai/free/en/papers/joty-2016-speech-act-modeling-written-asynchronous/)
203. [**Extending Implicit Discourse Relation Recognition to the PDTB-3**Li Liang, Zheng Zhao, Bonnie Webber*2020 · 25 citations*](https://md.research.elamur.ai/free/en/papers/liang-2020-extending-implicit-discourse-relation-recognition/)
204. [**Morphological Word Embeddings for Arabic Neural Machine Translation in Low-Resource Settings**Pamela Shapiro, Kevin Duh*2018 · 25 citations*](https://md.research.elamur.ai/free/en/papers/shapiro-2018-morphological-word-embeddings-arabic-neural/)
205. [**Automatic Arabic Dialect Identification Systems for Written Texts: A Survey**Maha J. Althobaiti*2020 · 24 citations*](https://md.research.elamur.ai/free/en/papers/althobaiti-2020-automatic-arabic-dialect-identification-systems/)
206. [**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/)
207. [**Weakly-Supervised Modeling of Contextualized Event Embedding for Discourse Relations**I-Ta Lee, Maria Leonor Pacheco, Dan Goldwasser*2020 · 23 citations*](https://md.research.elamur.ai/free/en/papers/lee-2020-weakly-supervised-modeling-contextualized-event/)
208. [**Rule- and Learning-based Methods for Bridging Resolution in the ARRAU Corpus**Ina Roesiger*2018 · 22 citations*](https://md.research.elamur.ai/free/en/papers/roesiger-2018-rule-learning-based-methods-bridging/)
209. [**Modeling Speech Acts in Asynchronous Conversations: A Neural-CRF Approach**Shafiq Joty, Tasnim Mohiuddin*2018 · 20 citations*](https://md.research.elamur.ai/free/en/papers/joty-2018-modeling-speech-acts-asynchronous-conversations/)
210. [**A Distributional and Orthographic Aggregation Model for English Derivational Morphology**Daniel Deutsch, John Hewitt, Dan Roth*2018 · 19 citations*](https://md.research.elamur.ai/free/en/papers/deutsch-2018-distributional-orthographic-aggregation-model-english/)
211. [**Applying Occam's Razor to Transformer-Based Dependency Parsing: What Works, What Doesn't, and What is Really Necessary**Stefan Grünewald, Annemarie Friedrich, Jonas Kuhn*2021 · 18 citations*](https://md.research.elamur.ai/free/en/papers/grunewald-2021-applying-occam-s-razor-transformer/)
212. [**AR-ASAG An ARabic Dataset for Automatic Short Answer Grading Evaluation**Leila Ouahrani, Djamal Bennouar*2020 · 18 citations*](https://md.research.elamur.ai/free/en/papers/ouahrani-2020-ar-asag-arabic-dataset-automatic/)
213. [**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/)
214. [**2*n is better than n²: Decomposing Event Coreference Resolution into Two Tractable Problems**Shafiuddin Rehan Ahmed, Abhijnan Nath, James H. Martin, et al.*2023 · 17 citations*](https://md.research.elamur.ai/free/en/papers/ahmed-2023-2-n-is-better-than/)
215. [**Neural Japanese Zero Anaphora Resolution using Smoothed Large-scale Case Frames with Word Embedding**Souta Yamashiro, Hitoshi Nishikawa, Takenobu Tokunaga*17 citations*](https://md.research.elamur.ai/free/en/papers/yamashiro-neural-japanese-zero-anaphora-resolution/)
216. [**Pragmatic inference of scalar implicature by LLMs**Ye-eun Cho, Seong mook Kim*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/cho-2024-pragmatic-inference-scalar-implicature-llms/)
217. [**SemLink 2.0: Chasing Lexical Resources**Kevin Stowe, Jenette Preciado, Kathryn Conger, et al.*2021 · 15 citations*](https://md.research.elamur.ai/free/en/papers/stowe-2021-semlink-2-0-chasing-lexical/)
218. [**Contextualized Embeddings for Connective Disambiguation in Shallow Discourse Parsing**René Knaebel, Manfred Stede*2020 · 15 citations*](https://md.research.elamur.ai/free/en/papers/knaebel-2020-contextualized-embeddings-connective-disambiguation-shallow/)
219. [**Deep Contextualized Pairwise Semantic Similarity for Arabic Language Questions**Hesham Al-Bataineh, Wael Farhan, Ahmad Mustafa, et al.*2019 · 15 citations*](https://md.research.elamur.ai/free/en/papers/al-bataineh-2019-deep-contextualized-pairwise-semantic-similarity/)
220. [**New Arabic Medical Dataset for Diseases Classification**Jaafar Hammoud, Aleksandra Vatian, Natalia Dobrenko, et al.*2021 · 14 citations*](https://md.research.elamur.ai/free/en/papers/hammoud-2021-new-arabic-medical-dataset-diseases/)
221. [**Projection-based Coreference Resolution Using Deep Syntax**Michal Novák, Anna Nedoluzhko, Zdeněk Žabokrtský*2017 · 14 citations*](https://md.research.elamur.ai/free/en/papers/novak-2017-projection-based-coreference-resolution-deep/)
222. [**Revisiting Selectional Preferences for Coreference Resolution**Benjamin Heinzerling, Nafise Sadat Moosavi, Michael Strube*2017 · 14 citations*](https://md.research.elamur.ai/free/en/papers/heinzerling-2017-revisiting-selectional-preferences-coreference-resolution/)
223. [**Sexism detection: The first corpus in Algerian dialect with a code-switching in Arabic/ French and English**Imane Guellil, Ahsan Adeel, Faical Azouaou, et al.*2021 · 12 citations*](https://md.research.elamur.ai/free/en/papers/guellil-2021-sexism-detection-first-corpus-algerian/)
224. [**Semantic properties of English nominal pluralization: Insights from word embeddings**Elnaz Shafaei-Bajestan, Masoumeh Moradipour-Tari, Peter Uhrig, et al.*2022 · 11 citations*](https://md.research.elamur.ai/free/en/papers/shafaei-bajestan-2022-semantic-properties-english-nominal-pluralization/)
225. [**On the Importance of Tokenization in Arabic Embedding Models**Mohamed Alkaoud, Mairaj Syed*2020 · 11 citations*](https://md.research.elamur.ai/free/en/papers/alkaoud-2020-importance-tokenization-arabic-embedding-models/)
226. [**Leveraging Pretrained Word Embeddings for Part-of-Speech Tagging of Code Switching Data**Fahad AlGhamdi, Mona Diab*2019 · 11 citations*](https://md.research.elamur.ai/free/en/papers/alghamdi-2019-leveraging-pretrained-word-embeddings-part/)
227. [**Adapting Event Embedding for Implicit Discourse Relation Recognition**Maria Leonor Pacheco, I-Ta Lee, Xiao Zhang, et al.*2016 · 11 citations*](https://md.research.elamur.ai/free/en/papers/pacheco-2016-adapting-event-embedding-implicit-discourse/)
228. [**Child-Directed Language Does Not Consistently Boost Syntax Learning in Language Models**Francesca Padovani, Jaap Jumelet, Yevgen Matusevych, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/padovani-2025-child-directed-language-does-not/)
229. [**YNU-HPCC at SemEval-2022 Task 6: Transformer-based Model for Intended Sarcasm Detection in English and Arabic**Guangmin Zheng, Jin Wang, Xuejie Zhang*2022 · 9 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2022-ynu-hpcc-semeval-2022-task/)
230. [**Transferring Monolingual Model to Low-Resource Language: The Case of Tigrinya**Abrhalei Tela; Abraham Woubie;, Ville Hautamaki*2020 · 9 citations*](https://md.research.elamur.ai/free/en/papers/tela-2020-transferring-monolingual-model-low-resource/)
231. [**IMS HotCoref DE: A Data-driven Co-reference Resolver for German**Ina Roesiger, Jonas Kuhn*2016 · 9 citations*](https://md.research.elamur.ai/free/en/papers/roesiger-2016-ims-hotcoref-de-data-driven/)
232. [**Multimodal Semantic Learning from Child-Directed Input**Angeliki Lazaridou, Grzegorz Chrupała, Raquel Fernández, et al.*2016 · 9 citations*](https://md.research.elamur.ai/free/en/papers/lazaridou-2016-multimodal-semantic-learning-child-directed/)
233. [**TArC: Tunisian Arabish Corpus, First complete release**Elisa Gugliotta, Marco Dinarelli*2022 · 8 citations*](https://md.research.elamur.ai/free/en/papers/gugliotta-2022-tarc-tunisian-arabish-corpus-first/)
234. [**Contextualized Embeddings for Enriching Linguistic Analyses on Politeness**Ahmad Aljanaideh, Eric Fosler-Lussier, Marie-Catherine de Marneffe*2020 · 8 citations*](https://md.research.elamur.ai/free/en/papers/aljanaideh-2020-contextualized-embeddings-enriching-linguistic-analyses/)
235. [**Evaluating Word Embeddings on Low-Resource Languages**Nathan Stringham, Mike Izbicki*2020 · 8 citations*](https://md.research.elamur.ai/free/en/papers/stringham-2020-evaluating-word-embeddings-low-resource/)
236. [**Multi-level Gated Recurrent Neural Network for dialog act classification**Wei Li, Yunfang Wu*2016 · 8 citations*](https://md.research.elamur.ai/free/en/papers/li-2016-multi-level-gated-recurrent-neural/)
237. [**Multimodal Cross-Document Event Coreference Resolution Using Linear Semantic Transfer and Mixed-Modality Ensembles**Abhijnan Nath, Huma Jamil, Shafiuddin Rehan Ahmed, et al.*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/nath-2024-multimodal-cross-document-event-coreference/)
238. [**Personality Analysis for Social Media Users using Arabic language and its Effect on Sentiment Analysis**Mokhaiber Dandash, Masoud Asadpour*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/dandash-2024-personality-analysis-social-media-users/)
239. [**Amharic Abstractive Text Summarization**Amr M. Zaki, Mahmoud I. Khalil, Hazem M. Abbas*2020 · 7 citations*](https://md.research.elamur.ai/free/en/papers/zaki-2020-amharic-abstractive-text-summarization/)
240. [**Combining Context-Free and Contextualized Representations for Arabic Sarcasm Detection and Sentiment Identification**Amey Hengle, Atharva Kshirsagar, Shaily Desai, et al.*2021 · 6 citations*](https://md.research.elamur.ai/free/en/papers/hengle-2021-combining-context-free-contextualized-representations/)
241. [**Exploring Tokenization Strategies and Vocabulary Sizes for Enhanced Arabic Language Models**Mohamed Taher Alrefaie, Nour Eldin Morsy, Nada Samir*2024 · 5 citations*](https://md.research.elamur.ai/free/en/papers/alrefaie-2024-exploring-tokenization-strategies-vocabulary-sizes/)
242. [**Improving Arabic Multi-Label Emotion Classification using Stacked Embeddings and Hybrid Loss Function**Muhammad Azeem Aslam, Wang Jun, Nisar Ahmed, et al.*2024 · 5 citations*](https://md.research.elamur.ai/free/en/papers/aslam-2024-improving-arabic-multi-label-emotion/)
243. [**ALADAN at IWSLT24 Low-resource Arabic Dialectal Speech Translation Task**Waad Ben Kheder, Josef Jon, André Beyer, et al.*2024 · 4 citations*](https://md.research.elamur.ai/free/en/papers/kheder-2024-aladan-iwslt24-low-resource-arabic/)
244. [**Detecting Syntactic Change Using a Neural Part-of-Speech Tagger**William Merrill, Gigi Stark, Robert Frank*2019 · 4 citations*](https://md.research.elamur.ai/free/en/papers/merrill-2019-detecting-syntactic-change-neural-part/)
245. [**Fixing the Infix: Unsupervised Discovery of Root-and-Pattern Morphology**Tarek Sakakini, Suma Bhat, Pramod Viswanath*2017 · 4 citations*](https://md.research.elamur.ai/free/en/papers/sakakini-2017-fixing-infix-unsupervised-discovery-root/)
246. [**Probabilistic Modelling of Morphologically Rich Languages**Jan A. Botha*2015 · 4 citations*](https://md.research.elamur.ai/free/en/papers/botha-2015-probabilistic-modelling-morphologically-rich-languages/)
247. [**Modeling the Evolution of English Noun Compounds with Feature-Rich Diachronic Compositionality Prediction**Filip Miletić, Sabine Schulte im Walde*2025 · 3 citations*](https://md.research.elamur.ai/free/en/papers/miletic-2025-modeling-evolution-english-noun-compounds/)
248. [**COMICORDA: Dialogue Act Recognition in Comic Books**Jiri Martinek, Pavel Kral, Ladislav Lenc, et al.*2024 · 3 citations*](https://md.research.elamur.ai/free/en/papers/martinek-2024-comicorda-dialogue-act-recognition-comic/)
249. [**Prompting Instruction-tuned LLMs for Semantic Similarity Values**Xander Akiko Snelder, Yunchong Huang, Jelke Bloem*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/snelder-2026-prompting-instruction-tuned-llms-semantic/)
250. [**Evaluation of Semantic Search and its Role in Retrieved-Augmented-Generation (RAG) for Arabic Language**Ali Mahboub, Muhy Eddin Za'ter, Bashar Al-Rfooh, et al.*2024 · 2 citations*](https://md.research.elamur.ai/free/en/papers/mahboub-2024-evaluation-semantic-search-role-retrieved/)
251. [**Fine-Tashkeel: Finetuning Byte-Level Models for Accurate Arabic Text Diacritization**Bashar Al-Rfooh, Gheith Abandah, Rami Al-Rfou*2023 · 2 citations*](https://md.research.elamur.ai/free/en/papers/al-rfooh-2023-fine-tashkeel-finetuning-byte-level/)
252. [**Improving Natural Language Inference in Arabic using Transformer Models and Linguistically Informed Pre-Training**Mohammad Majd Saad Al Deen, Maren Pielka, Jorn Hees, et al.*2023 · 2 citations*](https://md.research.elamur.ai/free/en/papers/deen-2023-improving-natural-language-inference-arabic/)
253. [**Comparing Native and Learner Englishes Using a Large Pre-trained Language Model**Tatsuya Aoyama*2022 · 2 citations*](https://md.research.elamur.ai/free/en/papers/aoyama-2022-comparing-native-learner-englishes-large/)
254. [**Roadblocks in Gender Bias Measurement for Diachronic Corpora**Saied Alshahrani, Esma Wali, Abdullah R Alshamsan, et al.*2022 · 2 citations*](https://md.research.elamur.ai/free/en/papers/alshahrani-2022-roadblocks-gender-bias-measurement-diachronic/)
255. [**Evaluating Universal Dependency Parser Recovery of Predicate Argument Structure via CompChain Analysis**Sagar Indurkhya, Beracah Yankama, Robert C. Berwick*2021 · 2 citations*](https://md.research.elamur.ai/free/en/papers/indurkhya-2021-evaluating-universal-dependency-parser-recovery/)
256. [**Sarcasm and Sentiment Detection in Arabic: investigating the interest of character-level features**Dhaou Ghoul, Gaël Lejeune*2021 · 2 citations*](https://md.research.elamur.ai/free/en/papers/ghoul-2021-sarcasm-sentiment-detection-arabic-investigating/)
257. [**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/)
258. [**Transparent Semantic Change Detection with Dependency-Based Profiles**Bach Phan Tat, Kris Heylen, Dirk Geeraerts, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/tat-2026-transparent-semantic-change-detection-dependency/)
259. [**Word-Embeddings Distinguish Denominal and Root-Derived Verbs in Semitic**Ido Benbaji, Omri Doron, Adele Henot-Mortier*2022 · 1 citation*](https://md.research.elamur.ai/free/en/papers/benbaji-2022-word-embeddings-distinguish-denominal-root/)
260. [**Effect of Word Embedding Variable Parameters on Arabic Sentiment Analysis Performance**Anwar Alnawas, Nursal ARICI*2021 · 1 citation*](https://md.research.elamur.ai/free/en/papers/alnawas-2021-effect-word-embedding-variable-parameters/)
261. [**Thematic role assignment in non-default verb classes: A cross-linguistic comparison of English and German**Louise Kyriaki, Matthias Schlesewsky, Ina Bornkessel-Schlesewsky*2021 · 1 citation*](https://md.research.elamur.ai/free/en/papers/kyriaki-2021-thematic-role-assignment-non-default/)
262. [**Prepositional Phrase Attachment over Word Embedding Products**Pranava Swaroop Madhyastha, Xavier Carreras, Ariadna Quattoni*2017 · 1 citation*](https://md.research.elamur.ai/free/en/papers/madhyastha-2017-prepositional-phrase-attachment-over-word/)
263. [**A Transparent Model of Syntactic and Semantic Cue-based Retrieval**Shisen Yue, John T. Hale*2026*](https://md.research.elamur.ai/free/en/papers/yue-2026-transparent-model-syntactic-semantic-cue/)
264. [**Explore Political Discourse with Transformers. Emergent Paradigmatic and Syntagmatic Representations.**Laurent Vanni, Damon Mayaffre*2026*](https://md.research.elamur.ai/free/en/papers/vanni-2026-explore-political-discourse-transformers-emergent/)
265. [**LST at MWE-2026 AdMIRe 2: Advancing Multimodal Idiomaticity Representation**Le Qiu, Yu-Yin Hsu, Emmanuele Chersoni*2026*](https://md.research.elamur.ai/free/en/papers/qiu-2026-lst-mwe-2026-admire-2/)
266. [**Modeling semantic association in self-paced reading with language model embeddings**Sara Møller Østergaard, Kenneth Enevoldsen, Afra Alishahi, et al.*2026*](https://md.research.elamur.ai/free/en/papers/ostergaard-2026-modeling-semantic-association-self-paced/)
267. [**One Word Is Not Enough: Simple Prompts Improve Word Embeddings**Rajeev Ranjan*2026*](https://md.research.elamur.ai/free/en/papers/ranjan-2026-one-word-is-not-enough/)
268. [**Onomasiological Sense Alignment Across Dialect Dictionaries. A Taxonomy-Constrained LLM Classification**Nathalie Mederake, Nico Urbach, Hanna Fischer, et al.*2026*](https://md.research.elamur.ai/free/en/papers/mederake-2026-onomasiological-sense-alignment-across-dialect/)
269. [**Predicting Topic (Co-)Occurrence Using Topic Networks Built from the Project Gutenberg Corpus**Bhuvanesh Verma, Alexander Mehler*2026*](https://md.research.elamur.ai/free/en/papers/verma-2026-predicting-topic-co-occurrence-topic/)
270. [**Push and Pull: Training Sentence Encoders with Contrastive Losses for Distance-Based Multi-Label Text Classification**Jens Van Nooten, Andriy Kosar*2026*](https://md.research.elamur.ai/free/en/papers/nooten-2026-push-pull-training-sentence-encoders/)
271. [**Semantic Factor Analysis: Validating Personality Structure Recovery from empirically-mediated Word Embeddings**Oliver Müller*2026*](https://md.research.elamur.ai/free/en/papers/muller-2026-semantic-factor-analysis-validating-personality/)
272. [**Sentiment Analysis and Language Models for Kwanyama**Ndapa Nakashole*2026*](https://md.research.elamur.ai/free/en/papers/nakashole-2026-sentiment-analysis-language-models-kwanyama/)
273. [**Sentiment Classification of Gaza War Headlines: A Comparative Analysis of Large Language Models and Arabic Fine-Tuned BERT Models**Amr Eleraqi; Hager H. Mustafa;, Abdul Hadi N. Ahmed*2026*](https://md.research.elamur.ai/free/en/papers/eleraqi-2026-sentiment-classification-gaza-war-headlines/)
274. [**The Impact of Tokenization Algorithms on Hungarian Language Model Performance**Mátyás Osváth, Máté Norbert Molnár, Roland Gunics, et al.*2026*](https://md.research.elamur.ai/free/en/papers/osvath-2026-impact-tokenization-algorithms-hungarian-language/)
275. [**What Are LLMs Doing to Scientific Communication? Measuring Changes in Writing Practices and Reading Experience**Filip Miletić, Neele Falk*2026*](https://md.research.elamur.ai/free/en/papers/miletic-2026-what-are-llms-doing-scientific/)
276. [**Wiktionary as a Crowdsourced Lexicon for English Dialects**Sidney Wong*2026*](https://md.research.elamur.ai/free/en/papers/wong-2026-wiktionary-crowdsourced-lexicon-english-dialects/)
277. [**Non Idiomatic Conventionalised Expressions: A New Pain in the Neck?**Ganesh Katrapati, Manish Shrivastava*2025*](https://md.research.elamur.ai/free/en/papers/katrapati-2025-non-idiomatic-conventionalised-expressions-new/)
278. [**Robustness Evaluation of ChatGPT Against Chinese Adversarial Attacks (中文对抗攻击下的ChatGPT鲁棒性评估)**Yunting Zhang (张云婷), Lin Ye (叶麟), Baisong Li (李柏松), et al.*2025*](https://md.research.elamur.ai/free/en/papers/zhang-2025-robustness-evaluation-chatgpt/)
279. [**Universal Dependencies for Sindhi**John Bauer, Sakiina Shah, Muhammad Shaheer, et al.*2025*](https://md.research.elamur.ai/free/en/papers/bauer-2025-universal-dependencies-sindhi/)
280. [**Survey on Representation Learning Methods of Knowledge Graph for Link Prediction (面向链接预测的知识图谱表示学习方法综述)**Xueying Du (杜雪盈), Mingwei Liu (刘名威), Liwei Shen (沈立炜), et al.*2023*](https://md.research.elamur.ai/free/en/papers/du-2023-representation-learning-methods/)
281. [**The Truth, The Whole Truth, and Nothing but the Truth: A New Benchmark Dataset for Hebrew Text Credibility Assessment**Ben Hagag, Reut Tsarfaty*2023*](https://md.research.elamur.ai/free/en/papers/hagag-2023-truth-whole-truth-nothing-but/)
282. [**What to Make of make? Sense Distinctions for Light Verbs**Julie Kallini, Christiane Fellbaum*2023*](https://md.research.elamur.ai/free/en/papers/kallini-2023-what-make-make-sense-distinctions/)
283. [**A Deep CNN Architecture with Novel Pooling Layer Applied to Two Sudanese Arabic Sentiment Datasets**Mustafa Mhamed, Richard Sutcliffe, Xia Sun, et al.*2022*](https://md.research.elamur.ai/free/en/papers/mhamed-2022-deep-cnn-architecture-novel-pooling/)
284. [**Overview on Knowledge Graph Embedding Technology Research (知识图谱嵌入技术研究综述)**Tiancheng Zhang (张天成), Xue Tian (田雪), Xianghui Sun (孙相会), et al.*2021*](https://md.research.elamur.ai/free/en/papers/zhang-2021-overview-knowledge-graph/)
285. [**The semantic transparency of English compound nouns**Martin Schäfer*2018*](https://md.research.elamur.ai/free/en/papers/schafer-2018-semantic-transparency-english-compound/)

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

3,561 more papers of our library cite it; they have no page here yet.

- [← 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