---
title: "Who cites Raquel Urtasun — page 3 — 1,942 citing papers"
description: "1942 papers of the Elamur Research library cite the works of Raquel Urtasun, found in their bibliographies · page 3 of 4 · 201–300; the most…"
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---
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# Who cites Raquel Urtasun

2,065 citations of their works from 1,942 papers of our library (of the 149,439 whose bibliographies we read) · 327 with a page here, the most cited first · page 3 of 4 · 201–300 · [← Raquel Urtasun](https://md.research.elamur.ai/free/en/authors/raquel-urtasun/)

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201. **[Discourse Parsing with Attention-based Hierarchical Neural Networks](https://md.research.elamur.ai/free/en/papers/li-2016-discourse-parsing-attention-based-hierarchical/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Qi Li, Tianshi Li, Baobao Chang*2016 · 150 citations*
202. **[HyperLex: A Large-Scale Evaluation of Graded Lexical Entailment](https://md.research.elamur.ai/free/en/papers/vulic-2017-hyperlex-large-scale-evaluation-graded/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Ivan Vulić, Daniela Gerz, Douwe Kiela, et al.*2017 · 148 citations*
203. **[Text Embeddings Reveal (Almost) As Much As Text](https://md.research.elamur.ai/free/en/papers/morris-2023-text-embeddings-reveal-almost-as/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**John Morris, Volodymyr Kuleshov, Vitaly Shmatikov, et al.*2023 · 147 citations*
204. **[Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders](https://md.research.elamur.ai/free/en/papers/liu-2021-fast-effective-self-supervised-transforming/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Fangyu Liu, Ivan Vulić, Anna Korhonen, et al.*2021 · 147 citations*
205. **[Neural Net Models of Open-domain Discourse Coherence](https://md.research.elamur.ai/free/en/papers/li-2017-neural-net-models-open-domain/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiwei Li, Dan Jurafsky*2017 · 147 citations*
206. **[RUSE: Regressor Using Sentence Embeddings for Automatic Machine Translation Evaluation](https://md.research.elamur.ai/free/en/papers/shimanaka-2018-ruse-regressor-sentence-embeddings-automatic/) [Conference on Machine Translation: Shared Task Papers](https://md.research.elamur.ai/free/en/venues/conference-on-machine-translation-shared-task-papers/)**Hiroki Shimanaka, Tomoyuki Kajiwara, Mamoru Komachi*2018 · 141 citations*
207. **[Paragraph-level Simplification of Medical Texts](https://md.research.elamur.ai/free/en/papers/devaraj-2021-paragraph-level-simplification-medical-texts/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ashwin Devaraj, Iain Marshall, Byron Wallace, et al.*2021 · 140 citations*
208. **[UER: An Open-Source Toolkit for Pre-training Models](https://md.research.elamur.ai/free/en/papers/zhao-2019-uer-open-source-toolkit-pre/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhe Zhao, Hui Chen, Jinbin Zhang, et al.*2019 · 140 citations*
209. [**Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches arXiv:1904.01172**Shane Storks, Qiaozi Gao, Joyce Y. Chai*2019 · 135 citations*](https://md.research.elamur.ai/free/en/papers/storks-2019-recent-advances-natural-language-inference/)
210. **[DisSent: Learning Sentence Representations from Explicit Discourse Relations](https://md.research.elamur.ai/free/en/papers/nie-2019-dissent-learning-sentence-representations-explicit/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Allen Nie, Erin Bennett, Noah Goodman*2019 · 134 citations*
211. [**EuroLLM: Multilingual Language Models for Europe arXiv:2409.16235**Pedro Henrique Martins, Patrick Fernandes, Joao Alves, et al.*2024 · 133 citations*](https://md.research.elamur.ai/free/en/papers/martins-2024-eurollm-multilingual-language-models-europe/)
212. **[Linguistic Features for Readability Assessment](https://md.research.elamur.ai/free/en/papers/deutsch-2020-linguistic-features-readability-assessment/) [Workshop on Innovative Use of NLP for Building Educational Applications (BEA)](https://md.research.elamur.ai/free/en/venues/bea/)**Tovly Deutsch, Masoud Jasbi, Stuart Shieber*2020 · 130 citations*
213. [**A Comprehensive Assessment of Dialog Evaluation Metrics The First Workshop on Evaluations and Assessments of Neural Conversation Systems**Yi-Ting Yeh, Maxine Eskenazi, Shikib Mehri*2021 · 128 citations*](https://md.research.elamur.ai/free/en/papers/yeh-2021-comprehensive-assessment-dialog-evaluation-metrics/)
214. [**Nomic Embed: Training a Reproducible Long Context Text Embedder arXiv:2402.01613**Zach Nussbaum, John X. Morris, Brandon Duderstadt, et al.*2024 · 126 citations*](https://md.research.elamur.ai/free/en/papers/nussbaum-2024-nomic-embed-training-reproducible-long/)
215. **[Learning Dense Representations of Phrases at Scale](https://md.research.elamur.ai/free/en/papers/lee-2021-learning-dense-representations-phrases-scale/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinhyuk Lee, Mujeen Sung, Jaewoo Kang, et al.*2021 · 126 citations*
216. **[Learning Distributed Representations of Texts and Entities from Knowledge Base](https://md.research.elamur.ai/free/en/papers/yamada-2017-learning-distributed-representations-texts-entities/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ikuya Yamada, Hiroyuki Shindo, Hideaki Takeda, et al.*2017 · 125 citations*
217. **[Knowledge of cultural moral norms in large language models](https://md.research.elamur.ai/free/en/papers/ramezani-2023-knowledge-cultural-moral-norms-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aida Ramezani, Yang Xu*2023 · 120 citations*
218. [**Pretrained Encyclopedia: Weakly Supervised Knowledge-Pretrained Language Model arXiv:1912.09637**Wenhan Xiong, Jingfei Du, William Yang Wang, et al.*2019 · 117 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2019-pretrained-encyclopedia-weakly-supervised-knowledge/)
219. [**Physics of Language Models: Part 3.1, Knowledge Storage and Extraction arXiv:2309.14316**Zeyuan Allen-Zhu, Yuanzhi Li*2023 · 116 citations*](https://md.research.elamur.ai/free/en/papers/allen-zhu-2023-physics-language-models-part-3/)
220. **[SlideVQA: A Dataset for Document Visual Question Answering on Multiple Images](https://md.research.elamur.ai/free/en/papers/tanaka-2023-slidevqa-dataset-document-visual-question/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Ryota Tanaka, Kyosuke Nishida, Kosuke Nishida, et al.*2023 · 116 citations*
221. [**Branch-Train-Merge: Embarrassingly Parallel Training of Expert Language Models arXiv:2208.03306**Margaret Li, Suchin Gururangan, Tim Dettmers, et al.*2022 · 114 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-branch-train-merge-embarrassingly-parallel/)
222. [**Efficient Large Scale Language Modeling with Mixtures of Experts arXiv:2112.10684**Mikel Artetxe, Shruti Bhosale, Naman Goyal, et al.*2021 · 113 citations*](https://md.research.elamur.ai/free/en/papers/artetxe-2021-efficient-large-scale-language-modeling/)
223. [**Parallel Iterative Edit Models for Local Sequence Transduction arXiv:1910.02893**Abhijeet Awasthi, Sunita Sarawagi, Rasna Goyal, et al.*2019 · 112 citations*](https://md.research.elamur.ai/free/en/papers/awasthi-2019-parallel-iterative-edit-models-local/)
224. **[What's in the Box? An Analysis of Undesirable Content in the Common Crawl Corpus](https://md.research.elamur.ai/free/en/papers/luccioni-2021-what-s-box-analysis-undesirable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Alexandra Luccioni, Joseph Viviano*2021 · 111 citations*
225. **[Copyright Violations and Large Language Models](https://md.research.elamur.ai/free/en/papers/karamolegkou-2023-copyright-violations-large-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Antonia Karamolegkou, Jiaang Li, Li Zhou, et al.*2023 · 109 citations*
226. [**A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity arXiv:2305.13169**Shayne Longpre, Gregory Yauney, Emily Reif, et al.*2023 · 104 citations*](https://md.research.elamur.ai/free/en/papers/longpre-2023-pretrainer-s-guide-training-data/)
227. [**AnglE-optimized Text Embeddings arXiv:2309.12871**Xianming Li, Jing Li*2023 · 103 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-angle-optimized-text-embeddings/)
228. [**minicons: Enabling Flexible Behavioral and Representational Analyses of Transformer Language Models arXiv:2203.13112**Kanishka Misra*2022 · 102 citations*](https://md.research.elamur.ai/free/en/papers/misra-2022-minicons-enabling-flexible-behavioral-representational/)
229. [**Are Transformers universal approximators of sequence-to-sequence functions? arXiv:1912.10077**Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat, et al.*2019 · 97 citations*](https://md.research.elamur.ai/free/en/papers/yun-2019-transformers-universal-approximators-sequence-sequence/)
230. **[Probing Across Time: What Does RoBERTa Know and When?](https://md.research.elamur.ai/free/en/papers/liu-2021-probing-across-time-what-does/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Leo Z. Liu, Yizhong Wang, Jungo Kasai, et al.*2021 · 96 citations*
231. **[LinCE: A Centralized Benchmark for Linguistic Code-switching Evaluation](https://md.research.elamur.ai/free/en/papers/aguilar-2020-lince-centralized-benchmark-linguistic-code/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Gustavo Aguilar, Sudipta Kar, Thamar Solorio*2020 · 96 citations*
232. **[CoDraw: Collaborative Drawing as a Testbed for Grounded Goal-driven Communication](https://md.research.elamur.ai/free/en/papers/kim-2019-codraw-collaborative-drawing-as-testbed/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jin-Hwa Kim, Nikita Kitaev, Xinlei Chen, et al.*2019 · 94 citations*
233. **[Frequency Effects on Syntactic Rule Learning in Transformers](https://md.research.elamur.ai/free/en/papers/wei-2021-frequency-effects-syntactic-rule-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jason Wei, Dan Garrette, Tal Linzen, et al.*2021 · 92 citations*
234. **[BERT Busters: Outlier Dimensions that Disrupt Transformers](https://md.research.elamur.ai/free/en/papers/kovaleva-2021-bert-busters-outlier-dimensions-that/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Olga Kovaleva, Saurabh Kulshreshtha, Anna Rogers, et al.*2021 · 90 citations*
235. **[LVBench: An Extreme Long Video Understanding Benchmark](https://md.research.elamur.ai/free/en/papers/wang-2024-lvbench-extreme-long-video-understanding/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Weihan Wang, Zehai He, Wenyi Hong, et al.*2024 · 89 citations*
236. **[Dialogue Act Classification with Context-Aware Self-Attention](https://md.research.elamur.ai/free/en/papers/raheja-2019-dialogue-act-classification-context-aware/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Vipul Raheja, Joel Tetreault*2019 · 89 citations*
237. **[hULMonA: The Universal Language Model in Arabic](https://md.research.elamur.ai/free/en/papers/eljundi-2019-hulmona-universal-language-model-arabic/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Obeida ElJundi, Wissam Antoun, Nour El Droubi, et al.*2019 · 89 citations*
238. [**A Survey of Large Language Models in Medicine: Progress, Application, and Challenge arXiv:2311.05112**Hongjian Zhou, Fenglin Liu, Boyang Gu, et al.*2023 · 87 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-survey-large-language-models-medicine/)
239. **[BlonDe: An Automatic Evaluation Metric for Document-level Machine Translation](https://md.research.elamur.ai/free/en/papers/jiang-2022-blonde-automatic-evaluation-metric-document/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yuchen Jiang, Tianyu Liu, Shuming Ma, et al.*2022 · 85 citations*
240. **[ORCA: A Challenging Benchmark for Arabic Language Understanding](https://md.research.elamur.ai/free/en/papers/elmadany-2023-orca-challenging-benchmark-arabic-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**AbdelRahim Elmadany, ElMoatez Billah Nagoudi, Muhammad Abdul-Mageed*2023 · 83 citations*
241. **[Mining Discourse Markers for Unsupervised Sentence Representation Learning](https://md.research.elamur.ai/free/en/papers/sileo-2019-mining-discourse-markers-unsupervised-sentence/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Damien Sileo, Tim Van De Cruys, Camille Pradel, et al.*2019 · 83 citations*
242. **[D4: Improving LLM Pretraining via Document De-Duplication and Diversification](https://md.research.elamur.ai/free/en/papers/tirumala-2023-d4-improving-llm-pretraining-document/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Kushal Tirumala, Daniel Simig, Armen Aghajanyan, et al.*2023 · 81 citations*
243. **[A Systematic Study of Neural Discourse Models for Implicit Discourse Relation](https://md.research.elamur.ai/free/en/papers/rutherford-2017-systematic-study-neural-discourse-models/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Attapol Rutherford, Vera Demberg, Nianwen Xue*2017 · 78 citations*
244. [**Repetition Improves Language Model Embeddings arXiv:2402.15449**Jacob Mitchell Springer, Suhas Kotha, Daniel Fried, et al.*2024 · 73 citations*](https://md.research.elamur.ai/free/en/papers/springer-2024-repetition-improves-language-model-embeddings/)
245. [**ClinicalGPT: Large Language Models Finetuned with Diverse Medical Data and Comprehensive Evaluation arXiv:2306.09968**Guangyu Wang, Guoxing Yang, Zongxin Du, et al.*2023 · 70 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-clinicalgpt-large-language-models-finetuned/)
246. **[How Furiously Can Colorless Green Ideas Sleep? Sentence Acceptability in Context](https://md.research.elamur.ai/free/en/papers/lau-2020-how-furiously-can-colorless-green/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jey Han Lau, Carlos Armendariz, Shalom Lappin, et al.*2020 · 69 citations*
247. **[A Thorough Examination of Decoding Methods in the Era of LLMs](https://md.research.elamur.ai/free/en/papers/shi-2024-thorough-examination-decoding-methods-era/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chufan Shi, Haoran Yang, Deng Cai, et al.*2024 · 68 citations*
248. **[Characterizing the dynamics of learning in repeated reference games](https://md.research.elamur.ai/free/en/papers/hawkins-2019-characterizing-dynamics-learning-repeated-reference/) [Cognitive Science](https://md.research.elamur.ai/free/en/venues/cognitive-science/)**Robert D. Hawkins, Michael C. Frank, Noah D. Goodman*2019 · 67 citations*
249. **[Multi-Relational Script Learning for Discourse Relations](https://md.research.elamur.ai/free/en/papers/lee-2019-multi-relational-script-learning-discourse/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**I-Ta Lee, Dan Goldwasser*2019 · 66 citations*
250. **[Idiom Token Classification using Sentential Distributed Semantics](https://md.research.elamur.ai/free/en/papers/salton-2016-idiom-token-classification-sentential-distributed/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Giancarlo Salton, Robert Ross, John Kelleher*2016 · 65 citations*
251. **[Automatic Story Generation: Challenges and Attempts](https://md.research.elamur.ai/free/en/papers/alabdulkarim-2021-automatic-story-generation-challenges-attempts/) [Workshop on Narrative Understanding](https://md.research.elamur.ai/free/en/venues/nuse/)**Amal Alabdulkarim, Siyan Li, Xiangyu Peng*2021 · 61 citations*
252. [**English Machine Reading Comprehension Datasets: A Survey**Daria Dzendzik, Jennifer Foster, Carl Vogel*2021 · 54 citations*](https://md.research.elamur.ai/free/en/papers/dzendzik-2021-english-machine-reading-comprehension-datasets/)
253. [**EuroLLM-9B: Technical Report arXiv:2506.04079**Pedro Henrique Martins, Joao Alves, Patrick Fernandes, et al.*2025 · 45 citations*](https://md.research.elamur.ai/free/en/papers/martins-2025-eurollm-9b-technical-report/)
254. **[SciNLI: A Corpus for Natural Language Inference on Scientific Text](https://md.research.elamur.ai/free/en/papers/sadat-2022-scinli-corpus-natural-language-inference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mobashir Sadat, Cornelia Caragea*2022 · 43 citations*
255. **[The ROOTS Search Tool: Data Transparency for LLMs](https://md.research.elamur.ai/free/en/papers/piktus-2023-roots-search-tool-data-transparency/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aleksandra Piktus, Christopher Akiki, Paulo Villegas, et al.*2023 · 42 citations*
256. **[Story Realization: Expanding Plot Events into Sentences](https://md.research.elamur.ai/free/en/papers/ammanabrolu-2019-story-realization-expanding-plot-events/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Prithviraj Ammanabrolu, Ethan Tien, Wesley Cheung, et al.*2019 · 42 citations*
257. **[Exploring Joint Neural Model for Sentence Level Discourse Parsing and Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/nejat-2017-exploring-joint-neural-model-sentence/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Bita Nejat, Giuseppe Carenini, Raymond Ng*2017 · 40 citations*
258. **[Reasoning Abilities of Large Language Models: In-Depth Analysis on the Abstraction and Reasoning Corpus](https://md.research.elamur.ai/free/en/papers/lee-2024-reasoning-abilities-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Seungpil Lee, Woochang Sim, Donghyeon Shin, et al.*2024 · 38 citations*
259. [**Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language Models arXiv:2305.09955**Shangbin Feng, Weijia Shi, Yuyang Bai, et al.*2023 · 35 citations*](https://md.research.elamur.ai/free/en/papers/feng-2023-knowledge-card-filling-llms-knowledge/)
260. [**M3KE: A Massive Multi-Level Multi-Subject Knowledge Evaluation Benchmark for Chinese Large Language Models arXiv:2305.10263**Chuang Liu, Renren Jin, Yuqi Ren, et al.*2023 · 34 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-m3ke-massive-multi-level/)
261. **[An Enhanced Latent Semantic Analysis Approach for Arabic Document Summarization](https://md.research.elamur.ai/free/en/papers/al-sabahi-2018-enhanced-latent-semantic-analysis-approach/) [Arabian Journal for Science and Engineering](https://md.research.elamur.ai/free/en/venues/arabian-journal-for-science-and-engineering/)**Kamal Al-Sabahi, Zuping Zhang, Jun Long, et al.*2018 · 33 citations*
262. **[Evaluating Document Coherence Modeling](https://md.research.elamur.ai/free/en/papers/shen-2021-evaluating-document-coherence-modeling/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Aili Shen, Meladel Mistica, Bahar Salehi, et al.*2021 · 30 citations*
263. [**Pushing the Limits of ChatGPT on NLP Tasks arXiv:2306.09719**Xiaofei Sun, Linfeng Dong, Xiaoya Li, et al.*2023 · 28 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-pushing-limits-chatgpt-nlp-tasks/)
264. [**ERNIE-Doc: A Retrospective Long-Document Modeling Transformer arXiv:2012.15688**Siyu Ding, Junyuan Shang, Shuohuan Wang, et al.*2020 · 27 citations*](https://md.research.elamur.ai/free/en/papers/ding-2020-ernie-doc-retrospective-long/)
265. **[Detecting Multilingual COVID-19 Misinformation on Social Media via Contextualized Embeddings](https://md.research.elamur.ai/free/en/papers/panda-2021-detecting-multilingual-covid-19-misinformation/) [Workshop on NLP for Internet Freedom: Censorship, Disinformation, and Propaganda](https://md.research.elamur.ai/free/en/venues/nlp4if/)**Subhadarshi Panda, Sarah Ita Levitan*2021 · 25 citations*
266. **[A closer look at the performance of neural language models on reflexive anaphor licensing](https://md.research.elamur.ai/free/en/papers/hu-2020-closer-look-performance-neural-language/) [Society for Computation in Linguistics (SCiL)](https://md.research.elamur.ai/free/en/venues/scil/)**Jennifer Hu, Sherry Yong Chen, Roger Levy*2020 · 24 citations*
267. **[Predicting In-Game Actions from Interviews of NBA Players](https://md.research.elamur.ai/free/en/papers/oved-2020-predicting-game-actions-interviews-nba/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Nadav Oved, Amir Feder, Roi Reichart*2020 · 24 citations*
268. **[Finding Convincing Arguments Using Scalable Bayesian Preference Learning](https://md.research.elamur.ai/free/en/papers/simpson-2018-finding-convincing-arguments-scalable-bayesian/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Edwin Simpson, Iryna Gurevych*2018 · 24 citations*
269. [**MacBERTh: Development and Evaluation of a Historically Pre-trained Language Model for English (1450-1950)**Enrique Manjavacas Arevalo, Lauren Fonteyn*2021 · 23 citations*](https://md.research.elamur.ai/free/en/papers/arevalo-2021-macberth-development-evaluation-historically-pre/)
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271. [**ERNIE-Gram: Pre-Training with Explicitly N-Gram Masked Language Modeling for Natural Language Understanding arXiv:2010.12148**Dongling Xiao, Yu-Kun Li, Han Zhang, et al.*2020 · 22 citations*](https://md.research.elamur.ai/free/en/papers/xiao-2020-ernie-gram-pre-training/)
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275. [**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/)
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296. [**Explicit Pairwise Word Interaction Modeling Improves Pretrained Transformers for English Semantic Similarity Tasks arXiv:1911.02847**Yinan Zhang, Raphael Tang, Jimmy Lin*2019 · 6 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2019-explicit-pairwise-word-interaction-modeling/)
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