---
title: "Who cites Greg S. Corrado — page 3"
description: "8,086 papers of the Elamur Research library cite the works of Greg S. Corrado, found in their bibliographies · page 3 of 7 · 201–300; the most cited first."
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---
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# Who cites Greg S. Corrado

9,133 citations of their works from 8,086 papers of our library (of the 140,884 whose bibliographies we read) · 618 with a page here, the most cited first · page 3 of 7 · 201–300 · [← Greg S. Corrado](https://md.research.elamur.ai/free/en/authors/greg-s-corrado/)

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201. [**Embedding Entities and Relations for Learning and Inference in Knowledge Bases**Bishan Yang, Wen-tau Yih, Xiaodong He, et al.*2014 · 458 citations*](https://md.research.elamur.ai/free/en/papers/yang-2014-embedding-entities-relations-learning-inference/)
202. [**Emergent: a novel data-set for stance classification**William Ferreira, Andreas Vlachos*2016 · 456 citations*](https://md.research.elamur.ai/free/en/papers/ferreira-2016-emergent-novel-data-set-stance/)
203. [**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/)
204. [**Large language models are few-shot clinical information extractors**Monica Agrawal, Stefan Hegselmann, Hunter Lang, et al.*2022 · 448 citations*](https://md.research.elamur.ai/free/en/papers/agrawal-2022-large-language-models-are-few/)
205. [**CARER: Contextualized Affect Representations for Emotion Recognition**Elvis Saravia, Hsien-Chi Toby Liu, Yen-Hao Huang, et al.*2018 · 448 citations*](https://md.research.elamur.ai/free/en/papers/saravia-2018-carer-contextualized-affect-representations-emotion/)
206. [**Multi-Perspective Sentence Similarity Modeling with Convolutional Neural Networks**Hua He, Kevin Gimpel, Jimmy Lin*2015 · 447 citations*](https://md.research.elamur.ai/free/en/papers/he-2015-multi-perspective-sentence-similarity-modeling/)
207. [**HIBERT: Document Level Pre-training of Hierarchical Bidirectional Transformers for Document Summarization**Xingxing Zhang, Furu Wei, Ming Zhou*2019 · 446 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2019-hibert-document-level-pre-training/)
208. [**Pretrained Transformers Improve Out-of-Distribution Robustness**Dan Hendrycks, Xiaoyuan Liu, Eric Wallace, et al.*2020 · 442 citations*](https://md.research.elamur.ai/free/en/papers/hendrycks-2020-pretrained-transformers-improve-out-distribution/)
209. [**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/)
210. [**The Falcon Series of Open Language Models**Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.*2023 · 436 citations*](https://md.research.elamur.ai/free/en/papers/almazrouei-2023-falcon-series-open-language-models/)
211. [**SemEval 2017 Task 10: ScienceIE - Extracting Keyphrases and Relations from Scientific Publications**Isabelle Augenstein, Mrinal Das, Sebastian Riedel, et al.*2017 · 435 citations*](https://md.research.elamur.ai/free/en/papers/augenstein-2017-semeval-2017-task-10-scienceie/)
212. [**Improving Text Embeddings with Large Language Models**Liang Wang, Nan Yang, Xiaolong Huang, et al.*2024 · 433 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-improving-text-embeddings-large-language/)
213. [**One-step and Two-step Classification for Abusive Language Detection on Twitter**Ji Ho Park, Pascale Fung*2017 · 433 citations*](https://md.research.elamur.ai/free/en/papers/park-2017-one-step-two-step-classification/)
214. [**Unsupervised Statistical Machine Translation**Mikel Artetxe, Gorka Labaka, Eneko Agirre*2018 · 432 citations*](https://md.research.elamur.ai/free/en/papers/artetxe-2018-unsupervised-statistical-machine-translation/)
215. [**Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora**William L. Hamilton, Kevin Clark, Jure Leskovec, et al.*2016 · 431 citations*](https://md.research.elamur.ai/free/en/papers/hamilton-2016-inducing-domain-specific-sentiment-lexicons/)
216. [**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/)
217. [**Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation**Ikuya Yamada, Hiroyuki Shindo, Hideaki Takeda, et al.*2016 · 427 citations*](https://md.research.elamur.ai/free/en/papers/yamada-2016-joint-learning-embedding-words-entities/)
218. [**Benchmarking Retrieval-Augmented Generation for Medicine**Guangzhi Xiong, Qiao Jin, Zhiyong Lu, et al.*2024 · 426 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2024-benchmarking-retrieval-augmented-generation-medicine/)
219. [**Offline bilingual word vectors, orthogonal transformations and the inverted softmax**Samuel L. Smith, David H. P. Turban, Steven Hamblin, et al.*2017 · 426 citations*](https://md.research.elamur.ai/free/en/papers/smith-2017-offline-bilingual-word-vectors-orthogonal/)
220. [**Natural Language Inference by Tree-Based Convolution and Heuristic Matching**Lili Mou, Rui Men, Ge Li, et al.*2016 · 425 citations*](https://md.research.elamur.ai/free/en/papers/mou-2016-natural-language-inference-tree-based/)
221. [**Improving Coreference Resolution by Learning Entity-Level Distributed Representations**Kevin Clark, Christopher D. Manning*2016 · 422 citations*](https://md.research.elamur.ai/free/en/papers/clark-2016-improving-coreference-resolution-learning-entity/)
222. [**Empower Sequence Labeling with Task-Aware Neural Language Model**Liyuan Liu, Jingbo Shang, Frank F. Xu, et al.*2017 · 419 citations*](https://md.research.elamur.ai/free/en/papers/liu-2017-empower-sequence-labeling-task-aware/)
223. [**ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learning**Viet Dac Lai, Nghia Ngo, Amir Pouran Ben Veyseh, et al.*2023 · 418 citations*](https://md.research.elamur.ai/free/en/papers/lai-2023-chatgpt-beyond-english-comprehensive-evaluation/)
224. [**Tailoring Continuous Word Representations for Dependency Parsing**Mohit Bansal, Kevin Gimpel, Karen Livescu*2014 · 418 citations*](https://md.research.elamur.ai/free/en/papers/bansal-2014-tailoring-continuous-word-representations-dependency/)
225. [**Adversarial Training Methods for Semi-Supervised Text Classification**Takeru Miyato, Andrew M. Dai, Ian Goodfellow*2016 · 416 citations*](https://md.research.elamur.ai/free/en/papers/miyato-2016-adversarial-training-methods-semi-supervised/)
226. [**PPDB 2.0: Better paraphrase ranking, fine-grained entailment relations, word embeddings, and style classification**Ellie Pavlick, Pushpendre Rastogi, Juri Ganitkevitch, et al.*2015 · 414 citations*](https://md.research.elamur.ai/free/en/papers/pavlick-2015-ppdb-2-0-better-paraphrase/)
227. [**Unsupervised Neural Machine Translation**Mikel Artetxe, Gorka Labaka, Eneko Agirre, et al.*2017 · 410 citations*](https://md.research.elamur.ai/free/en/papers/artetxe-2017-unsupervised-neural-machine-translation/)
228. [**Multi-Turn Response Selection for Chatbots with Deep Attention Matching Network**Xiangyang Zhou, Lu Li, Daxiang Dong, et al.*2018 · 408 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2018-multi-turn-response-selection-chatbots/)
229. [**BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains**Yanis Labrak, Adrien Bazoge, Emmanuel Morin, et al.*2024 · 406 citations*](https://md.research.elamur.ai/free/en/papers/labrak-2024-biomistral-collection-open-source-pretrained/)
230. [**Generating Sentences by Editing Prototypes**Kelvin Guu, Tatsunori B. Hashimoto, Yonatan Oren, et al.*2017 · 404 citations*](https://md.research.elamur.ai/free/en/papers/guu-2017-generating-sentences-editing-prototypes/)
231. [**Social Biases in NLP Models as Barriers for Persons with Disabilities**Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, et al.*2020 · 402 citations*](https://md.research.elamur.ai/free/en/papers/hutchinson-2020-social-biases-nlp-models-as/)
232. [**Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning**Mitchell Gordon, Kevin Duh, Nicholas Andrews*2020 · 400 citations*](https://md.research.elamur.ai/free/en/papers/gordon-2020-compressing-bert-studying-effects-weight/)
233. [**How to Fine-Tune BERT for Text Classification?**Chi Sun, Xipeng Qiu, Yige Xu, et al.*2019 · 400 citations*](https://md.research.elamur.ai/free/en/papers/sun-2019-fine-tune-bert-text-classification/)
234. [**Massively Multilingual Word Embeddings**Waleed Ammar, George Mulcaire, Yulia Tsvetkov, et al.*2016 · 399 citations*](https://md.research.elamur.ai/free/en/papers/ammar-2016-massively-multilingual-word-embeddings/)
235. [**Disentangled Representation Learning for Non-Parallel Text Style Transfer**Vineet John, Lili Mou, Hareesh Bahuleyan, et al.*2019 · 396 citations*](https://md.research.elamur.ai/free/en/papers/john-2019-disentangled-representation-learning-non-parallel/)
236. [**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/)
237. [**Gender Bias in Neural Natural Language Processing**Kaiji Lu, Piotr Mardziel, Fangjing Wu, et al.*2018 · 394 citations*](https://md.research.elamur.ai/free/en/papers/lu-2018-gender-bias-neural-natural-language/)
238. [**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/)
239. [**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/)
240. [**Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms**Dinghan Shen, Guoyin Wang, Wenlin Wang, et al.*2018 · 383 citations*](https://md.research.elamur.ai/free/en/papers/shen-2018-baseline-needs-more-love-simple/)
241. [**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/)
242. [**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/)
243. [**Open Sesame: Getting inside BERT's Linguistic Knowledge**Yongjie Lin, Yi Chern Tan, Robert Frank*2019 · 379 citations*](https://md.research.elamur.ai/free/en/papers/lin-2019-open-sesame-getting-inside-bert/)
244. [**Chinese Poetry Generation with Recurrent Neural Networks**Xingxing Zhang, Mirella Lapata*2014 · 376 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2014-chinese-poetry-generation-recurrent-neural/)
245. [**CAIL2018: A Large-Scale Legal Dataset for Judgment Prediction**Chaojun Xiao, Haoxi Zhong, Zhipeng Guo, et al.*2018 · 375 citations*](https://md.research.elamur.ai/free/en/papers/xiao-2018-cail2018-large-scale-legal-dataset/)
246. [**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/)
247. [**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/)
248. [**Improving Lexical Embeddings with Semantic Knowledge**Mo Yu, Mark Dredze*2014 · 371 citations*](https://md.research.elamur.ai/free/en/papers/yu-2014-improving-lexical-embeddings-semantic-knowledge/)
249. [**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/)
250. [**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/)
251. [**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/)
252. [**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/)
253. [**Identifying and Reducing Gender Bias in Word-Level Language Models**Shikha Bordia, Samuel R. Bowman*2019 · 363 citations*](https://md.research.elamur.ai/free/en/papers/bordia-2019-identifying-reducing-gender-bias-word/)
254. [**Combining Language and Vision with a Multimodal Skip-gram Model**Angeliki Lazaridou, Nghia The Pham, Marco Baroni*2015 · 362 citations*](https://md.research.elamur.ai/free/en/papers/lazaridou-2015-combining-language-vision-multimodal-skip/)
255. [**Adversarial Training for Unsupervised Bilingual Lexicon Induction**Meng Zhang, Yang Liu, Huanbo Luan, et al.*2017 · 359 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2017-adversarial-training-unsupervised-bilingual-lexicon/)
256. [**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/)
257. [**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/)
258. [**Adversarial Removal of Demographic Attributes from Text Data**Yanai Elazar, Yoav Goldberg*2018 · 357 citations*](https://md.research.elamur.ai/free/en/papers/elazar-2018-adversarial-removal-demographic-attributes-text/)
259. [**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/)
260. [**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/)
261. [**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/)
262. [**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/)
263. [**FiLM: Visual Reasoning with a General Conditioning Layer**Ethan Perez, Florian Strub, Harm de Vries, et al.*2017 · 348 citations*](https://md.research.elamur.ai/free/en/papers/perez-2017-film-visual-reasoning-general-conditioning/)
264. [**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/)
265. [**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/)
266. [**Graph-based Neural Multi-Document Summarization**Michihiro Yasunaga, Rui Zhang, Kshitijh Meelu, et al.*2017 · 346 citations*](https://md.research.elamur.ai/free/en/papers/yasunaga-2017-graph-based-neural-multi-document/)
267. [**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/)
268. [**Lessons from Natural Language Inference in the Clinical Domain**Alexey Romanov, Chaitanya Shivade*2018 · 343 citations*](https://md.research.elamur.ai/free/en/papers/romanov-2018-lessons-natural-language-inference-clinical/)
269. [**Generating Natural Questions About an Image**Nasrin Mostafazadeh, Ishan Misra, Jacob Devlin, et al.*2016 · 339 citations*](https://md.research.elamur.ai/free/en/papers/mostafazadeh-2016-generating-natural-questions-about-image/)
270. [**Visualizing and Measuring the Geometry of BERT**Andy Coenen, Emily Reif, Ann Yuan, et al.*2019 · 338 citations*](https://md.research.elamur.ai/free/en/papers/coenen-2019-visualizing-measuring-geometry-bert/)
271. [**Sentence Compression by Deletion with LSTMs**Katja Filippova, Enrique Alfonseca, Carlos A. Colmenares, et al.*2015 · 337 citations*](https://md.research.elamur.ai/free/en/papers/filippova-2015-sentence-compression-deletion-lstms/)
272. [**UL2: Unifying Language Learning Paradigms**Yi Tay, Mostafa Dehghani, Vinh Q. Tran, et al.*2022 · 334 citations*](https://md.research.elamur.ai/free/en/papers/tay-2022-ul2-unifying-language-learning-paradigms/)
273. [**Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT**Akshay Smit, Saahil Jain, Pranav Rajpurkar, et al.*2020 · 334 citations*](https://md.research.elamur.ai/free/en/papers/smit-2020-combining-automatic-labelers-expert-annotations/)
274. [**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/)
275. [**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/)
276. [**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/)
277. [**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/)
278. [**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/)
279. [**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/)
280. [**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/)
281. [**Poincaré Embeddings for Learning Hierarchical Representations**Maximilian Nickel, Douwe Kiela*2017 · 324 citations*](https://md.research.elamur.ai/free/en/papers/nickel-2017-poincare-embeddings-learning-hierarchical-representations/)
282. [**Cultural Shift or Linguistic Drift? Comparing Two Computational Measures of Semantic Change**William L. Hamilton, Jure Leskovec, Dan Jurafsky*2016 · 324 citations*](https://md.research.elamur.ai/free/en/papers/hamilton-2016-cultural-shift-or-linguistic-drift/)
283. [**Probing Pretrained Language Models for Lexical Semantics**Ivan Vulić, Edoardo Maria Ponti, Robert Litschko, et al.*2020 · 320 citations*](https://md.research.elamur.ai/free/en/papers/vulic-2020-probing-pretrained-language-models-lexical/)
284. [**Improving Hypernymy Detection with an Integrated Path-based and Distributional Method**Vered Shwartz, Yoav Goldberg, Ido Dagan*2016 · 319 citations*](https://md.research.elamur.ai/free/en/papers/shwartz-2016-improving-hypernymy-detection-integrated-path/)
285. [**Joint Extraction of Events and Entities within a Document Context**Bishan Yang, Tom M. Mitchell*2016 · 317 citations*](https://md.research.elamur.ai/free/en/papers/yang-2016-joint-extraction-events-entities-within/)
286. [**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/)
287. [**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/)
288. [**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/)
289. [**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/)
290. [**Unsupervised Pretraining for Sequence to Sequence Learning**Prajit Ramachandran, Peter Liu, Quoc Le*2017 · 312 citations*](https://md.research.elamur.ai/free/en/papers/ramachandran-2017-unsupervised-pretraining-sequence-sequence-learning/)
291. [**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/)
292. [**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/)
293. [**MEDITRON-70B: Scaling Medical Pretraining for Large Language Models**Zeming Chen, Alejandro Hernandez Cano, Angelika Romanou, et al.*2023 · 307 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-meditron-70b-scaling-medical-pretraining/)
294. [**Good-Enough Compositional Data Augmentation**Jacob Andreas*2020 · 305 citations*](https://md.research.elamur.ai/free/en/papers/andreas-2020-good-enough-compositional-data-augmentation/)
295. [**UDPipe 2.0 Prototype at CoNLL 2018 UD Shared Task**Milan Straka*2018 · 303 citations*](https://md.research.elamur.ai/free/en/papers/straka-2018-udpipe-2-0-prototype-conll/)
296. [**AugGPT: Leveraging ChatGPT for Text Data Augmentation**Haixing Dai; Zhengliang Liu; Wenxiong Liao; Xiaoke Huang; Yihan Cao; Zihao Wu; Lin Zhao; Shaochen Xu; Wei Liu; Ninghao Liu; Sheng Li; Dajiang Zhu; Hongmin Cai; Lichao Sun; Quanzheng Li; Dinggang Shen; Tianming Liu;, Xiang Li*2023 · 302 citations*](https://md.research.elamur.ai/free/en/papers/dai-2023-auggpt-leveraging-chatgpt-text-data/)
297. [**Finding Function in Form: Compositional Character Models for Open Vocabulary Word Representation**Wang Ling, Tiago Luis, Luis Marujo, et al.*2015 · 301 citations*](https://md.research.elamur.ai/free/en/papers/ling-2015-finding-function-form-compositional-character/)
298. [**Challenges and Applications of Large Language Models**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 300 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
299. [**OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models**Yuliang Liu, Zhang Li, Mingxin Huang, et al.*2023 · 297 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-ocrbench-hidden-mystery-ocr-large/)
300. [**S2ORC: The Semantic Scholar Open Research Corpus**Kyle Lo, Lucy Lu Wang, Mark Neumann, et al.*2019 · 297 citations*](https://md.research.elamur.ai/free/en/papers/lo-2019-s2orc-semantic-scholar-open-research/)

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