---
title: "Who cites Greg S. Corrado — page 4"
description: "8,086 papers of the Elamur Research library cite the works of Greg S. Corrado, found in their bibliographies · page 4 of 7 · 301–400; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/greg-s-corrado/cited-by/page/4/"
---
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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 4 of 7 · 301–400 · [← Greg S. Corrado](https://md.research.elamur.ai/free/en/authors/greg-s-corrado/)

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301. [**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/)
302. [**Matching the Blanks: Distributional Similarity for Relation Learning**Livio Baldini Soares, Nicholas FitzGerald, Jeffrey Ling, et al.*2019 · 294 citations*](https://md.research.elamur.ai/free/en/papers/soares-2019-matching-blanks-distributional-similarity-relation/)
303. [**FlauBERT: Unsupervised Language Model Pre-training for French**Hang Le, Loïc Vial, Jibril Frej, et al.*2019 · 293 citations*](https://md.research.elamur.ai/free/en/papers/le-2019-flaubert-unsupervised-language-model-pre/)
304. [**Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little**Koustuv Sinha, Robin Jia, Dieuwke Hupkes, et al.*2021 · 292 citations*](https://md.research.elamur.ai/free/en/papers/sinha-2021-masked-language-modeling-distributional-hypothesis/)
305. [**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/)
306. [**A Benchmark Dataset for Learning to Intervene in Online Hate Speech**Jing Qian, Anna Bethke, Yinyin Liu, et al.*2019 · 290 citations*](https://md.research.elamur.ai/free/en/papers/qian-2019-benchmark-dataset-learning-intervene-online/)
307. [**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/)
308. [**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/)
309. [**Detecting Sarcasm in Multimodal Social Platforms**Rossano Schifanella, Paloma de Juan, Joel Tetreault, et al.*2016 · 289 citations*](https://md.research.elamur.ai/free/en/papers/schifanella-2016-detecting-sarcasm-multimodal-social-platforms/)
310. [**Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language**Andy Zeng, Maria Attarian, Brian Ichter, et al.*2022 · 285 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2022-socratic-models-composing-zero-shot/)
311. [**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/)
312. [**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/)
313. [**HuatuoGPT, Towards Taming Language Model to Be a Doctor**Hongbo Zhang, Junying Chen, Feng Jiang, et al.*2023 · 279 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-huatuogpt-taming-language-model-be/)
314. [**Ranking Sentences for Extractive Summarization with Reinforcement Learning**Shashi Narayan, Shay B. Cohen, Mirella Lapata*2018 · 279 citations*](https://md.research.elamur.ai/free/en/papers/narayan-2018-ranking-sentences-extractive-summarization-reinforcement/)
315. [**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/)
316. [**Llemma: An Open Language Model For Mathematics**Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, et al.*2023 · 275 citations*](https://md.research.elamur.ai/free/en/papers/azerbayev-2023-llemma-open-language-model-mathematics/)
317. [**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/)
318. [**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/)
319. [**Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Models**Ashwin K Vijayakumar, Michael Cogswell, Ramprasath R. Selvaraju, et al.*2016 · 266 citations*](https://md.research.elamur.ai/free/en/papers/vijayakumar-2016-diverse-beam-search-decoding-diverse/)
320. [**Summarizing Opinions: Aspect Extraction Meets Sentiment Prediction and They Are Both Weakly Supervised**Stefanos Angelidis, Mirella Lapata*2018 · 265 citations*](https://md.research.elamur.ai/free/en/papers/angelidis-2018-summarizing-opinions-aspect-extraction-meets/)
321. [**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/)
322. [**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/)
323. [**Distinguish Confusing Law Articles for Legal Judgment Prediction**Nuo Xu, Pinghui Wang, Long Chen, et al.*2020 · 258 citations*](https://md.research.elamur.ai/free/en/papers/xu-2020-distinguish-confusing-law-articles-legal/)
324. [**CLIFF: Contrastive Learning for Improving Faithfulness and Factuality in Abstractive Summarization**Shuyang Cao, Lu Wang*2021 · 257 citations*](https://md.research.elamur.ai/free/en/papers/cao-2021-cliff-contrastive-learning-improving-faithfulness/)
325. [**Automatic Text Scoring Using Neural Networks**Dimitrios Alikaniotis, Helen Yannakoudakis, Marek Rei*2016 · 257 citations*](https://md.research.elamur.ai/free/en/papers/alikaniotis-2016-automatic-text-scoring-neural-networks/)
326. [**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/)
327. [**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/)
328. [**A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification**Ye Zhang, Byron Wallace*2017 · 254 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2017-sensitivity-analysis-practitioners-guide-convolutional/)
329. [**Measuring and Reducing Gendered Correlations in Pre-trained Models**Kellie Webster, Xuezhi Wang, Ian Tenney, et al.*2020 · 252 citations*](https://md.research.elamur.ai/free/en/papers/webster-2020-measuring-reducing-gendered-correlations-pre/)
330. [**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/)
331. [**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/)
332. [**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/)
333. [**Interpreting Pretrained Contextualized Representations via Reductions to Static Embeddings**Rishi Bommasani, Kelly Davis, Claire Cardie*2020 · 248 citations*](https://md.research.elamur.ai/free/en/papers/bommasani-2020-interpreting-pretrained-contextualized-representations-reductions/)
334. [**Linear Algebraic Structure of Word Senses, with Applications to Polysemy**Sanjeev Arora, Yuanzhi Li, Yingyu Liang, et al.*2018 · 247 citations*](https://md.research.elamur.ai/free/en/papers/arora-2018-linear-algebraic-structure-word-senses/)
335. [**MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning**Xiangru Tang, Anni Zou, Zhuosheng Zhang, et al.*2024 · 244 citations*](https://md.research.elamur.ai/free/en/papers/tang-2024-medagents-large-language-models-as/)
336. [**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/)
337. [**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/)
338. [**CLUE: A Chinese Language Understanding Evaluation Benchmark**Liang Xu, Hai Hu, Xuanwei Zhang, et al.*2020 · 242 citations*](https://md.research.elamur.ai/free/en/papers/xu-2020-clue-chinese-language-understanding/)
339. [**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/)
340. [**Pretrained Language Models for Biomedical and Clinical Tasks: Understanding and Extending the State-of-the-Art**Patrick Lewis, Myle Ott, Jingfei Du, et al.*2020 · 240 citations*](https://md.research.elamur.ai/free/en/papers/lewis-2020-pretrained-language-models-biomedical-clinical/)
341. [**Arabic natural language processing: An overview**Imane Guellil, Houda Saadane, Faical Azouaou, et al.*2019 · 239 citations*](https://md.research.elamur.ai/free/en/papers/guellil-2019-arabic-natural-language-processing-overview/)
342. [**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/)
343. [**Humanity's Last Exam**Long Phan, Alice Gatti, Ziwen Han, et al.*2025 · 235 citations*](https://md.research.elamur.ai/free/en/papers/phan-2025-humanity-s-last-exam/)
344. [**Self-Guided Contrastive Learning for BERT Sentence Representations**Taeuk Kim, Kang Min Yoo, Sang-goo Lee*2021 · 234 citations*](https://md.research.elamur.ai/free/en/papers/kim-2021-self-guided-contrastive-learning-bert/)
345. [**Learning to Understand Phrases by Embedding the Dictionary**Felix Hill, Kyunghyun Cho, Anna Korhonen, et al.*2016 · 234 citations*](https://md.research.elamur.ai/free/en/papers/hill-2016-learning-understand-phrases-embedding-dictionary/)
346. [**Commonsense Knowledge Base Completion**Xiang Li, Aynaz Taheri, Lifu Tu, et al.*2016 · 232 citations*](https://md.research.elamur.ai/free/en/papers/li-2016-commonsense-knowledge-base-completion/)
347. [**From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood**Kelvin Guu, Panupong Pasupat, Evan Liu, et al.*2017 · 230 citations*](https://md.research.elamur.ai/free/en/papers/guu-2017-language-programs-bridging-reinforcement-learning/)
348. [**AlBERTo: Italian BERT Language Understanding Model for NLP Challenging Tasks Based on Tweets**Marco Polignano, Pierpaolo Basile, Marco de Gemmis, et al.*2019 · 228 citations*](https://md.research.elamur.ai/free/en/papers/polignano-2019-alberto-italian-bert-language-understanding/)
349. [**Cross-topic Argument Mining from Heterogeneous Sources**Christian Stab, Tristan Miller, Benjamin Schiller, et al.*2018 · 228 citations*](https://md.research.elamur.ai/free/en/papers/stab-2018-cross-topic-argument-mining-heterogeneous/)
350. [**A Language-Independent Neural Network for Event Detection**Xiaocheng Feng, Lifu Huang, Duyu Tang, et al.*2016 · 226 citations*](https://md.research.elamur.ai/free/en/papers/feng-2016-language-independent-neural-network-event/)
351. [**Evaluating Layers of Representation in Neural Machine Translation on Part-of-Speech and Semantic Tagging Tasks**Yonatan Belinkov, Lluis Marquez, Hassan Sajjad, et al.*2017 · 225 citations*](https://md.research.elamur.ai/free/en/papers/belinkov-2018-evaluating-layers-representation-neural-machine/)
352. [**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/)
353. [**GLUECoS: An Evaluation Benchmark for Code-Switched NLP**Simran Khanuja, Sandipan Dandapat, Anirudh Srinivasan, et al.*2020 · 222 citations*](https://md.research.elamur.ai/free/en/papers/khanuja-2020-gluecos-evaluation-benchmark-code-switched/)
354. [**Few-Shot Charge Prediction with Discriminative Legal Attributes**Zikun Hu, Xiang Li, Cunchao Tu, et al.*2018 · 221 citations*](https://md.research.elamur.ai/free/en/papers/hu-2018-few-shot-charge-prediction-discriminative/)
355. [**Steering Language Models With Activation Engineering**Alexander Matt Turner, Lisa Thiergart, Gavin Leech, et al.*2023 · 220 citations*](https://md.research.elamur.ai/free/en/papers/turner-2023-steering-language-models-activation-engineering/)
356. [**NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models**Chankyu Lee, Rajarshi Roy, Mengyao Xu, et al.*2024 · 219 citations*](https://md.research.elamur.ai/free/en/papers/lee-2024-nv-embed-improved-techniques-training/)
357. [**Med-HALT: Medical Domain Hallucination Test for Large Language Models**Ankit Pal, Logesh Kumar Umapathi, Malaikannan Sankarasubbu*2023 · 219 citations*](https://md.research.elamur.ai/free/en/papers/pal-2023-med-halt-medical-domain-hallucination/)
358. [**A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages**Pedro Javier Ortiz Suárez, Laurent Romary, Benoît Sagot*2020 · 219 citations*](https://md.research.elamur.ai/free/en/papers/suarez-2020-monolingual-approach-contextualized-word-embeddings/)
359. [**Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models**Neha Sengupta, Sunil Kumar Sahu, Bokang Jia, et al.*2023 · 217 citations*](https://md.research.elamur.ai/free/en/papers/sengupta-2023-jais-jais-chat-arabic-centric/)
360. [**The Argument Reasoning Comprehension Task: Identification and Reconstruction of Implicit Warrants**Ivan Habernal, Henning Wachsmuth, Iryna Gurevych, et al.*2018 · 217 citations*](https://md.research.elamur.ai/free/en/papers/habernal-2018-argument-reasoning-comprehension-task-identification/)
361. [**YiSi - a Unified Semantic MT Quality Evaluation and Estimation Metric for Languages with Different Levels of Available Resources**Chi-kiu Lo*2019 · 216 citations*](https://md.research.elamur.ai/free/en/papers/lo-2019-yisi-unified-semantic-mt-quality/)
362. [**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/)
363. [**Stochastic Language Generation in Dialogue using Recurrent Neural Networks with Convolutional Sentence Reranking**Tsung-Hsien Wen, Milica Gašić, Dongho Kim, et al.*2015 · 212 citations*](https://md.research.elamur.ai/free/en/papers/wen-2015-stochastic-language-generation-dialogue-recurrent/)
364. [**Syntax for Semantic Role Labeling, To Be, Or Not To Be**Shexia He, Zuchao Li, Hai Zhao, et al.*2018 · 211 citations*](https://md.research.elamur.ai/free/en/papers/he-2018-syntax-semantic-role-labeling-be/)
365. [**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/)
366. [**An Effective Approach to Unsupervised Machine Translation**Mikel Artetxe, Gorka Labaka, Eneko Agirre*2019 · 202 citations*](https://md.research.elamur.ai/free/en/papers/artetxe-2019-effective-approach-unsupervised-machine-translation/)
367. [**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/)
368. [**Retrieval of the Best Counterargument without Prior Topic Knowledge**Henning Wachsmuth, Shahbaz Syed, Benno Stein*2018 · 196 citations*](https://md.research.elamur.ai/free/en/papers/wachsmuth-2018-retrieval-best-counterargument-without-prior/)
369. [**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/)
370. [**Supervised and Unsupervised Neural Approaches to Text Readability**Matej Martinc, Senja Pollak, Marko Robnik-Šikonja*2021 · 190 citations*](https://md.research.elamur.ai/free/en/papers/martinc-2021-supervised-unsupervised-neural-approaches-text/)
371. [**A Dataset for Multi-Target Stance Detection**Parinaz Sobhani, Diana Inkpen, Xiaodan Zhu*2017 · 190 citations*](https://md.research.elamur.ai/free/en/papers/sobhani-2017-dataset-multi-target-stance-detection/)
372. [**When Being Unseen from mBERT is just the Beginning: Handling New Languages With Multilingual Language Models**Benjamin Muller, Antonios Anastasopoulos, Benoît Sagot, et al.*2021 · 189 citations*](https://md.research.elamur.ai/free/en/papers/muller-2021-when-being-unseen-mbert-is/)
373. [**Language Modelling Makes Sense: Propagating Representations through WordNet for Full-Coverage Word Sense Disambiguation**Daniel Loureiro, Alípio Jorge*2019 · 189 citations*](https://md.research.elamur.ai/free/en/papers/loureiro-2019-language-modelling-makes-sense-propagating/)
374. [**Gradient-based Adversarial Attacks against Text Transformers**Chuan Guo, Alexandre Sablayrolles, Hervé Jégou, et al.*2021 · 187 citations*](https://md.research.elamur.ai/free/en/papers/guo-2021-gradient-based-adversarial-attacks-against/)
375. [**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/)
376. [**Multilingual Jailbreak Challenges in Large Language Models**Yue Deng, Wenxuan Zhang, Sinno Jialin Pan, et al.*2023 · 183 citations*](https://md.research.elamur.ai/free/en/papers/deng-2023-multilingual-jailbreak-challenges-large-language/)
377. [**Knowledge Conflicts for LLMs: A Survey**Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.*2024 · 179 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-knowledge-conflicts-llms-survey/)
378. [**Charformer: Fast Character Transformers via Gradient-based Subword Tokenization**Yi Tay, Vinh Q. Tran, Sebastian Ruder, et al.*2021 · 179 citations*](https://md.research.elamur.ai/free/en/papers/tay-2021-charformer-fast-character-transformers-gradient/)
379. [**Representation Degeneration Problem in Training Natural Language Generation Models**Jun Gao, Di He, Xu Tan, et al.*2019 · 179 citations*](https://md.research.elamur.ai/free/en/papers/gao-2019-representation-degeneration-problem-training-natural/)
380. [**Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalization**Yu-Min Tseng, Yu-Chao Huang, Teng-Yun Hsiao, et al.*2024 · 177 citations*](https://md.research.elamur.ai/free/en/papers/tseng-2024-two-tales-persona-llms-survey/)
381. [**Evaluating Large Language Models: A Comprehensive Survey**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 177 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
382. [**Pre-training Multilingual Neural Machine Translation by Leveraging Alignment Information**Zehui Lin, Xiao Pan, Mingxuan Wang, et al.*2020 · 177 citations*](https://md.research.elamur.ai/free/en/papers/lin-2020-pre-training-multilingual-neural-machine/)
383. [**Magnets for Sarcasm: Making Sarcasm Detection Timely, Contextual and Very Personal**Aniruddha Ghosh, Tony Veale*2017 · 174 citations*](https://md.research.elamur.ai/free/en/papers/ghosh-2017-magnets-sarcasm-making-sarcasm-detection/)
384. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 169 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/)
385. [**Trankit: A Light-Weight Transformer-based Toolkit for Multilingual Natural Language Processing**Minh Van Nguyen, Viet Dac Lai, Amir Pouran Ben Veyseh, et al.*2021 · 169 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2021-trankit-light-weight-transformer-based/)
386. [**Generative Representational Instruction Tuning**Niklas Muennighoff, Hongjin Su, Liang Wang, et al.*2024 · 165 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2024-generative-representational-instruction-tuning/)
387. [**Style Transfer as Unsupervised Machine Translation**Zhirui Zhang, Shuo Ren, Shujie Liu, et al.*2018 · 164 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2018-style-transfer-unsupervised-machine-translation/)
388. [**AmericasNLI: Evaluating Zero-shot Natural Language Understanding of Pretrained Multilingual Models in Truly Low-resource Languages**Abteen Ebrahimi, Manuel Mager, Arturo Oncevay, et al.*2022 · 163 citations*](https://md.research.elamur.ai/free/en/papers/ebrahimi-2022-americasnli-evaluating-zero-shot-natural/)
389. [**Creating and Characterizing a Diverse Corpus of Sarcasm in Dialogue**Shereen Oraby, Vrindavan Harrison, Lena Reed, et al.*2016 · 163 citations*](https://md.research.elamur.ai/free/en/papers/oraby-2016-creating-characterizing-diverse-corpus-sarcasm/)
390. [**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/)
391. [**Shallow Convolutional Neural Network for Implicit Discourse Relation Recognition**Biao Zhang, Jinsong Su, Deyi Xiong, et al.*2015 · 161 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2015-shallow-convolutional-neural-network-implicit/)
392. [**Orca 2: Teaching Small Language Models How to Reason**Arindam Mitra, Luciano Del Corro, Shweti Mahajan, et al.*2023 · 160 citations*](https://md.research.elamur.ai/free/en/papers/mitra-2023-orca-2-teaching-small-language/)
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