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# Works of United Kingdom

707 · page 3 of 8 · the most cited first · [← United Kingdom](https://md.research.elamur.ai/free/en/countries/united-kingdom/)

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201. [**Anaphora and Discourse Structure**Bonnie Webber, Matthew Stone, Aravind Joshi, et al.*2003 · 315 citations*](https://md.research.elamur.ai/free/en/papers/webber-2003-anaphora-discourse-structure/)
202. [**Explainable Automated Fact-Checking for Public Health Claims**Neema Kotonya, Francesca Toni*2020 · 314 citations*](https://md.research.elamur.ai/free/en/papers/kotonya-2020-explainable-automated-fact-checking-public/)
203. [**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/)
204. [**ParaCrawl: Web-Scale Acquisition of Parallel Corpora**Marta Bañón, Pinzhen Chen, Barry Haddow, et al.*2020 · 308 citations*](https://md.research.elamur.ai/free/en/papers/banon-2020-paracrawl-web-scale-acquisition-parallel/)
205. [**Recognising Textual Entailment with Logical Inference**Johan Bos, Katja Markert*2005 · 306 citations*](https://md.research.elamur.ai/free/en/papers/bos-2005-recognising-textual-entailment-logical-inference/)
206. [**Challenges and frontiers in abusive content detection**Bertie Vidgen, Alex Harris, Dong Nguyen, et al.*2019 · 305 citations*](https://md.research.elamur.ai/free/en/papers/vidgen-2019-challenges-frontiers-abusive-content-detection/)
207. [**Automated Fact Checking: Task Formulations, Methods and Future Directions**James Thorne, Andreas Vlachos*2018 · 303 citations*](https://md.research.elamur.ai/free/en/papers/thorne-2018-automated-fact-checking-task-formulations/)
208. [**Abductive Commonsense Reasoning**Chandra Bhagavatula, Ronan Le Bras, Chaitanya Malaviya, et al.*2019 · 301 citations*](https://md.research.elamur.ai/free/en/papers/bhagavatula-2019-abductive-commonsense-reasoning/)
209. [**Near-Synonymy and Lexical Choice**Philip Edmonds, Graeme Hirst*2002 · 300 citations*](https://md.research.elamur.ai/free/en/papers/edmonds-2002-near-synonymy-lexical-choice/)
210. [**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/)
211. [**Copied Monolingual Data Improves Low-Resource Neural Machine Translation**Anna Currey, Antonio Valerio Miceli Barone, Kenneth Heafield*2017 · 296 citations*](https://md.research.elamur.ai/free/en/papers/currey-2017-copied-monolingual-data-improves-low/)
212. [**AdapterDrop: On the Efficiency of Adapters in Transformers**Andreas Rücklé, Gregor Geigle, Max Glockner, et al.*2021 · 294 citations*](https://md.research.elamur.ai/free/en/papers/ruckle-2021-adapterdrop-efficiency-adapters-transformers/)
213. [**A Corpus with Multi-Level Annotations of Patients, Interventions and Outcomes to Support Language Processing for Medical Literature**Benjamin Nye, Junyi Jessy Li, Roma Patel, et al.*2018 · 293 citations*](https://md.research.elamur.ai/free/en/papers/nye-2018-corpus-multi-level-annotations-patients/)
214. [**Information-Theoretic Probing for Linguistic Structure**Tiago Pimentel, Josef Valvoda, Rowan Hall Maudslay, et al.*2020 · 293 citations*](https://md.research.elamur.ai/free/en/papers/pimentel-2020-information-theoretic-probing-linguistic-structure/)
215. [**Prompting Large Language Model for Machine Translation: A Case Study**Biao Zhang, Barry Haddow, Alexandra Birch*2023 · 293 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-prompting-large-language-model-machine/)
216. [**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/)
217. [**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/)
218. [**Challenges and Strategies in Cross-Cultural NLP**Daniel Hershcovich, Stella Frank, Heather Lent, et al.*2022 · 290 citations*](https://md.research.elamur.ai/free/en/papers/hershcovich-2022-challenges-strategies-cross-cultural-nlp/)
219. [**Can You Put it All Together: Evaluating Conversational Agents' Ability to Blend Skills**Eric Michael Smith, Mary Williamson, Kurt Shuster, et al.*2020 · 288 citations*](https://md.research.elamur.ai/free/en/papers/smith-2020-can-you-put-it-all/)
220. [**MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning**Xiang Yue, Xingwei Qu, Ge Zhang, et al.*2023 · 288 citations*](https://md.research.elamur.ai/free/en/papers/yue-2023-mammoth-building-math-generalist-models/)
221. [**PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them**Patrick Lewis, Yuxiang Wu, Linqing Liu, et al.*2021 · 286 citations*](https://md.research.elamur.ai/free/en/papers/lewis-2021-paq-65-million-probably-asked/)
222. [**Learning to Paraphrase for Question Answering**Li Dong, Jonathan Mallinson, Siva Reddy, et al.*2017 · 285 citations*](https://md.research.elamur.ai/free/en/papers/dong-2017-learning-paraphrase-question-answering/)
223. [**Metaphor as a Medium for Emotion: An Empirical Study**Saif Mohammad, Ekaterina Shutova, Peter Turney*2016 · 285 citations*](https://md.research.elamur.ai/free/en/papers/mohammad-2016-metaphor-as-medium-emotion-empirical/)
224. [**Lexical Generalization in CCG Grammar Induction for Semantic Parsing**Tom Kwiatkowski, Luke Zettlemoyer, Sharon Goldwater, et al.*2011 · 283 citations*](https://md.research.elamur.ai/free/en/papers/kwiatkowski-2011-lexical-generalization-ccg-grammar-induction/)
225. [**Constructing Datasets for Multi-hop Reading Comprehension Across Documents**Johannes Welbl, Pontus Stenetorp, Sebastian Riedel*2018 · 283 citations*](https://md.research.elamur.ai/free/en/papers/welbl-2018-constructing-datasets-multi-hop-reading/)
226. [**Analysing Mathematical Reasoning Abilities of Neural Models**David Saxton, Edward Grefenstette, Felix Hill, et al.*2019 · 282 citations*](https://md.research.elamur.ai/free/en/papers/saxton-2019-analysing-mathematical-reasoning-abilities-neural/)
227. [**QuEst - A translation quality estimation framework**Lucia Specia, Kashif Shah, Jose G.C. de Souza, et al.*2013 · 281 citations*](https://md.research.elamur.ai/free/en/papers/specia-2013-quest-translation-quality-estimation-framework/)
228. [**Ragas: Automated Evaluation of Retrieval Augmented Generation**Shahul Es, Jithin James, Luis Espinosa-Anke, et al.*2023 · 280 citations*](https://md.research.elamur.ai/free/en/papers/es-2023-ragas-automated-evaluation-retrieval-augmented/)
229. [**Helping Our Own: The HOO 2011 Pilot Shared Task**Robert Dale, Adam Kilgarriff*2011 · 279 citations*](https://md.research.elamur.ai/free/en/papers/dale-2011-helping-our-own-hoo-2011/)
230. [**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/)
231. [**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/)
232. [**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/)
233. [**Kosmos-2: Grounding Multimodal Large Language Models to the World**Zhiliang Peng, Wenhui Wang, Li Dong, et al.*2023 · 272 citations*](https://md.research.elamur.ai/free/en/papers/peng-2023-kosmos-2-grounding-multimodal-large/)
234. [**XLM-T: Multilingual Language Models in Twitter for Sentiment Analysis and Beyond**Francesco Barbieri, Luis Espinosa Anke, Jose Camacho-Collados*2022 · 271 citations*](https://md.research.elamur.ai/free/en/papers/barbieri-2022-xlm-t-multilingual-language-models/)
235. [**ConveRT: Efficient and Accurate Conversational Representations from Transformers**Matthew Henderson, Iñigo Casanueva, Nikola Mrkšić, et al.*2020 · 267 citations*](https://md.research.elamur.ai/free/en/papers/henderson-2020-convert-efficient-accurate-conversational-representations/)
236. [**Weakly Supervised Learning for Hedge Classification in Scientific Literature**Ben Medlock, Ted Briscoe*2007 · 266 citations*](https://md.research.elamur.ai/free/en/papers/medlock-2007-weakly-supervised-learning-hedge-classification/)
237. [**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/)
238. [**SemEval-2016 Task 12: Clinical TempEval**Steven Bethard, Guergana Savova, Wei-Te Chen, et al.*2016 · 263 citations*](https://md.research.elamur.ai/free/en/papers/bethard-2016-semeval-2016-task-12-clinical/)
239. [**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/)
240. [**LexGLUE: A Benchmark Dataset for Legal Language Understanding in English**Ilias Chalkidis; Abhik Jana; Dirk Hartung; Michael Bommarito; Ion Androutsopoulos; Daniel Martin Katz;, Nikolaos Aletras*2021 · 256 citations*](https://md.research.elamur.ai/free/en/papers/chalkidis-2021-lexglue-benchmark-dataset-legal-language/)
241. [**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/)
242. [**Recurrent Convolutional Neural Networks for Discourse Compositionality**Nal Kalchbrenner, Phil Blunsom*2013 · 253 citations*](https://md.research.elamur.ai/free/en/papers/kalchbrenner-2013-recurrent-convolutional-neural-networks-discourse/)
243. [**Evaluating Discourse Phenomena in Neural Machine Translation**Rachel Bawden, Rico Sennrich, Alexandra Birch, et al.*2017 · 252 citations*](https://md.research.elamur.ai/free/en/papers/bawden-2017-evaluating-discourse-phenomena-neural-machine/)
244. [**On Coreferring: Coreference in MUC and Related Annotation Schemes**Kees van Deemter, Rodger Kibble*2000 · 252 citations*](https://md.research.elamur.ai/free/en/papers/deemter-2000-coreferring-coreference-muc-related-annotation/)
245. [**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/)
246. [**Neural Semantic Role Labeling with Dependency Path Embeddings**Michael Roth, Mirella Lapata*2016 · 251 citations*](https://md.research.elamur.ai/free/en/papers/roth-2016-neural-semantic-role-labeling-dependency/)
247. [**Personality Traits in Large Language Models**Greg Serapio-Garcia, Mustafa Safdari, Clement Crepy, et al.*2023 · 251 citations*](https://md.research.elamur.ai/free/en/papers/serapio-garcia-2023-personality-traits-large-language-models/)
248. [**SIMPLE: A General Framework for the Development of Multilingual Lexicons**Nuria Bel, Federica Busa, Nicoletta Calzolari, et al.*2000 · 250 citations*](https://md.research.elamur.ai/free/en/papers/bel-2000-simple-general-framework-development-multilingual/)
249. [**The Curse of Recursion: Training on Generated Data Makes Models Forget**Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao, et al.*2023 · 250 citations*](https://md.research.elamur.ai/free/en/papers/shumailov-2023-curse-recursion-training-generated-data/)
250. [**Metaphor Identification Using Verb and Noun Clustering**Ekaterina Shutova, Lin Sun, Anna Korhonen*2010 · 250 citations*](https://md.research.elamur.ai/free/en/papers/shutova-2010-metaphor-identification-verb-noun-clustering/)
251. [**Hallucinations in Large Multilingual Translation Models**Nuno M. Guerreiro, Duarte M. Alves, Jonas Waldendorf, et al.*2023 · 244 citations*](https://md.research.elamur.ai/free/en/papers/guerreiro-2023-hallucinations-large-multilingual-translation-models/)
252. [**Learning to Distinguish Hypernyms and Co-Hyponyms**Julie Weeds, Daoud Clarke, Jeremy Reffin, et al.*2014 · 242 citations*](https://md.research.elamur.ai/free/en/papers/weeds-2014-learning-distinguish-hypernyms-co-hyponyms/)
253. [**Factuality Challenges in the Era of Large Language Models**Isabelle Augenstein, Timothy Baldwin, Meeyoung Cha, et al.*2023 · 241 citations*](https://md.research.elamur.ai/free/en/papers/augenstein-2023-factuality-challenges-era-large-language/)
254. [**Large Language Monkeys: Scaling Inference Compute with Repeated Sampling**Bradley Brown, Jordan Juravsky, Ryan Ehrlich, et al.*2024 · 241 citations*](https://md.research.elamur.ai/free/en/papers/brown-2024-large-language-monkeys-scaling-inference/)
255. [**Simplifying Lexical Simplification: Do We Need Simplified Corpora?**Goran Glavaš, Sanja Štajner*2015 · 241 citations*](https://md.research.elamur.ai/free/en/papers/glavas-2015-simplifying-lexical-simplification-do-we/)
256. [**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/)
257. [**Multimodal Few-Shot Learning with Frozen Language Models**Maria Tsimpoukelli, Jacob Menick, Serkan Cabi, et al.*2021 · 238 citations*](https://md.research.elamur.ai/free/en/papers/tsimpoukelli-2021-multimodal-few-shot-learning-frozen/)
258. [**SemEval-2013 Task 7: The Joint Student Response Analysis and 8th Recognizing Textual Entailment Challenge**Myroslava Dzikovska, Rodney Nielsen, Chris Brew, et al.*2013 · 235 citations*](https://md.research.elamur.ai/free/en/papers/dzikovska-2013-semeval-2013-task-7-joint/)
259. [**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/)
260. [**Bayesian Word Sense Induction**Samuel Brody, Mirella Lapata*2009 · 234 citations*](https://md.research.elamur.ai/free/en/papers/brody-2009-bayesian-word-sense-induction/)
261. [**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/)
262. [**An Empirical Study on Compositionality in Compound Nouns**Siva Reddy, Diana McCarthy, Suresh Manandhar*2011 · 233 citations*](https://md.research.elamur.ai/free/en/papers/reddy-2011-empirical-study-compositionality-compound-nouns/)
263. [**How Context Affects Language Models' Factual Predictions**Fabio Petroni, Patrick Lewis, Aleksandra Piktus, et al.*2020 · 231 citations*](https://md.research.elamur.ai/free/en/papers/petroni-2020-context-affects-language-models-factual/)
264. [**Sarcasm Detection on Czech and English Twitter**Tomáš Ptáček, Ivan Habernal, Jun Hong*2014 · 230 citations*](https://md.research.elamur.ai/free/en/papers/ptacek-2014-sarcasm-detection-czech-english-twitter/)
265. [**CCAligned: A Massive Collection of Cross-Lingual Web-Document Pairs**Ahmed El-Kishky, Vishrav Chaudhary, Francisco Guzmán, et al.*2020 · 228 citations*](https://md.research.elamur.ai/free/en/papers/kishky-2020-ccaligned-massive-collection-cross-lingual/)
266. [**Findings of the Third Shared Task on Multimodal Machine Translation**Loïc Barrault, Fethi Bougares, Lucia Specia, et al.*2018 · 227 citations*](https://md.research.elamur.ai/free/en/papers/barrault-2018-findings-third-shared-task-multimodal/)
267. [**XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models**Paul Rottger, Hannah Rose Kirk, Bertie Vidgen, et al.*2023 · 227 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2023-xstest-test-suite-identifying-exaggerated/)
268. [**The University of Edinburgh's Neural MT Systems for WMT17**Rico Sennrich, Alexandra Birch, Anna Currey, et al.*2017 · 227 citations*](https://md.research.elamur.ai/free/en/papers/sennrich-2017-university-edinburgh-s-neural-mt/)
269. [**TrustLLM: Trustworthiness in Large Language Models**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 226 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
270. [**Interpretation of Natural Language Rules in Conversational Machine Reading**Marzieh Saeidi, Max Bartolo, Patrick Lewis, et al.*2018 · 225 citations*](https://md.research.elamur.ai/free/en/papers/saeidi-2018-interpretation-natural-language-rules-conversational/)
271. [**SLURP: A Spoken Language Understanding Resource Package**Emanuele Bastianelli, Andrea Vanzo, Pawel Swietojanski, et al.*2020 · 222 citations*](https://md.research.elamur.ai/free/en/papers/bastianelli-2020-slurp-spoken-language-understanding-resource/)
272. [**Specializing Smaller Language Models towards Multi-Step Reasoning**Yao Fu, Hao Peng, Litu Ou, et al.*2023 · 222 citations*](https://md.research.elamur.ai/free/en/papers/fu-2023-specializing-smaller-language-models-towards/)
273. [**The Bottom-up Evolution of Representations in the Transformer: A Study with Machine Translation and Language Modeling Objectives**Elena Voita, Rico Sennrich, Ivan Titov*2019 · 222 citations*](https://md.research.elamur.ai/free/en/papers/voita-2019-bottom-up-evolution-representations-transformer/)
274. [**Text Readability Assessment for Second Language Learners**Menglin Xia, Ekaterina Kochmar, Ted Briscoe*2016 · 222 citations*](https://md.research.elamur.ai/free/en/papers/xia-2016-text-readability-assessment-second-language/)
275. [**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/)
276. [**Two Contrasting Data Annotation Paradigms for Subjective NLP Tasks**Paul Röttger, Bertie Vidgen, Dirk Hovy, et al.*2022 · 219 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2022-two-contrasting-data-annotation-paradigms/)
277. [**Unsupervised Question Decomposition for Question Answering**Ethan Perez, Patrick Lewis, Wen-tau Yih, et al.*2020 · 218 citations*](https://md.research.elamur.ai/free/en/papers/perez-2020-unsupervised-question-decomposition-question-answering/)
278. [**FOLIO: Natural Language Reasoning with First-Order Logic**Simeng Han, Hailey Schoelkopf, Yilun Zhao, et al.*2022 · 217 citations*](https://md.research.elamur.ai/free/en/papers/han-2022-folio-natural-language-reasoning-first/)
279. [**Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing**Edoardo Maria Ponti, Helen O'Horan, Yevgeni Berzak, et al.*2019 · 217 citations*](https://md.research.elamur.ai/free/en/papers/ponti-2019-modeling-language-variation-universals-survey/)
280. [**Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning**Beliz Gunel, Jingfei Du, Alexis Conneau, et al.*2020 · 216 citations*](https://md.research.elamur.ai/free/en/papers/gunel-2020-supervised-contrastive-learning-pre-trained/)
281. [**Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models**Robert Logan IV, Ivana Balazevic, Eric Wallace, et al.*2022 · 215 citations*](https://md.research.elamur.ai/free/en/papers/iv-2022-cutting-down-prompts-parameters-simple/)
282. [**ASSET: A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformations**Fernando Alva-Manchego, Louis Martin, Antoine Bordes, et al.*2020 · 215 citations*](https://md.research.elamur.ai/free/en/papers/manchego-2020-asset-dataset-tuning-evaluation-sentence/)
283. [**Probing the Need for Visual Context in Multimodal Machine Translation**Ozan Caglayan, Pranava Madhyastha, Lucia Specia, et al.*2019 · 214 citations*](https://md.research.elamur.ai/free/en/papers/caglayan-2019-probing-need-visual-context-multimodal/)
284. [**N-gram Counts and Language Models from the Common Crawl**Christian Buck, Kenneth Heafield, Bas van Ooyen*2014 · 213 citations*](https://md.research.elamur.ai/free/en/papers/buck-2014-n-gram-counts-language-models/)
285. [**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/)
286. [**Accelerating scientific discovery with Co-Scientist**Juraj Gottweis, Wei-Hung Weng, Alexander Daryin, et al.*2025 · 212 citations*](https://md.research.elamur.ai/free/en/papers/gottweis-2025-accelerating-scientific-discovery-co/)
287. [**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/)
288. [**Teaching language models to support answers with verified quotes**Jacob Menick, Maja Trebacz, Vladimir Mikulik, et al.*2022 · 211 citations*](https://md.research.elamur.ai/free/en/papers/menick-2022-teaching-language-models-support-answers/)
289. [**SemEval-2012 Task 1: English Lexical Simplification**Lucia Specia, Sujay Kumar Jauhar, Rada Mihalcea*2012 · 210 citations*](https://md.research.elamur.ai/free/en/papers/specia-2012-semeval-2012-task-1-english/)
290. [**OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models**Anas Awadalla, Irena Gao, Josh Gardner, et al.*2023 · 209 citations*](https://md.research.elamur.ai/free/en/papers/awadalla-2023-openflamingo-open-source-framework-training/)
291. [**Learning Anaphoricity and Antecedent Ranking Features for Coreference Resolution**Sam Wiseman, Alexander M. Rush, Stuart Shieber, et al.*2015 · 209 citations*](https://md.research.elamur.ai/free/en/papers/wiseman-2015-learning-anaphoricity-antecedent-ranking-features/)
292. [**Compressing Context to Enhance Inference Efficiency of Large Language Models**Yucheng Li, Bo Dong, Frank Guerin, et al.*2023 · 208 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-compressing-context-enhance-inference-efficiency/)
293. [**Sources of Hallucination by Large Language Models on Inference Tasks**Nick McKenna, Tianyi Li, Liang Cheng, et al.*2023 · 208 citations*](https://md.research.elamur.ai/free/en/papers/mckenna-2023-sources-hallucination-large-language-models/)
294. [**PET: a Tool for Post-editing and Assessing Machine Translation**Wilker Aziz, Sheila Castilho, Lucia Specia*2012 · 206 citations*](https://md.research.elamur.ai/free/en/papers/aziz-2012-pet-tool-post-editing-assessing/)
295. [**Challenges in Detoxifying Language Models**Johannes Welbl, Amelia Glaese, Jonathan Uesato, et al.*2021 · 206 citations*](https://md.research.elamur.ai/free/en/papers/welbl-2021-challenges-detoxifying-language-models/)
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