---
title: "Who cites Deep Contextualized Word Representations — page 3"
description: "3,240 papers of the Elamur Research library cite «Deep Contextualized Word Representations», found in their bibliographies · page 3 of 4 · 201–300; the…"
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---
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# Who cites «Deep Contextualized Word Representations»

3,240 papers of our library cite it (of the 140,884 whose bibliographies we read) · 388 with a page here, the most cited first · page 3 of 4 · 201–300 · [← the paper](https://md.research.elamur.ai/free/en/papers/peters-2018-deep-contextualized-word-representations/)

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201. [**Structural Scaffolds for Citation Intent Classification in Scientific Publications**Arman Cohan, Waleed Ammar, Madeleine van Zuylen, et al.*2019 · 287 citations*](https://md.research.elamur.ai/free/en/papers/cohan-2019-structural-scaffolds-citation-intent-classification/)
202. [**Two are Better than One: Joint Entity and Relation Extraction with Table-Sequence Encoders**Jue Wang, Wei Lu*2020 · 286 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-two-are-better-than-one/)
203. [**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/)
204. [**Fine-grained Fact Verification with Kernel Graph Attention Network**Zhenghao Liu, Chenyan Xiong, Maosong Sun, et al.*2020 · 282 citations*](https://md.research.elamur.ai/free/en/papers/liu-2020-fine-grained-fact-verification-kernel/)
205. [**Jointly Predicting Predicates and Arguments in Neural Semantic Role Labeling**Luheng He, Kenton Lee, Omer Levy, et al.*2018 · 282 citations*](https://md.research.elamur.ai/free/en/papers/he-2018-jointly-predicting-predicates-arguments-neural/)
206. [**Multi-Sentence Argument Linking**Seth Ebner, Patrick Xia, Ryan Culkin, et al.*2020 · 281 citations*](https://md.research.elamur.ai/free/en/papers/ebner-2020-multi-sentence-argument-linking/)
207. [**BAM! Born-Again Multi-Task Networks for Natural Language Understanding**Kevin Clark, Minh-Thang Luong, Urvashi Khandelwal, et al.*2019 · 279 citations*](https://md.research.elamur.ai/free/en/papers/clark-2019-bam-born-again-multi-task/)
208. [**Text Classification Using Label Names Only: A Language Model Self-Training Approach**Yu Meng, Yunyi Zhang, Jiaxin Huang, et al.*2020 · 274 citations*](https://md.research.elamur.ai/free/en/papers/meng-2020-text-classification-label-names-only/)
209. [**Injecting Numerical Reasoning Skills into Language Models**Mor Geva, Ankit Gupta, Jonathan Berant*2020 · 268 citations*](https://md.research.elamur.ai/free/en/papers/geva-2020-injecting-numerical-reasoning-skills-into/)
210. [**IndoNLU: Benchmark and Resources for Evaluating Indonesian Natural Language Understanding**Bryan Wilie, Karissa Vincentio, Genta Indra Winata, et al.*2020 · 265 citations*](https://md.research.elamur.ai/free/en/papers/wilie-2020-indonlu-benchmark-resources-evaluating-indonesian/)
211. [**Towards Understanding and Mitigating Social Biases in Language Models**Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency, et al.*2021 · 263 citations*](https://md.research.elamur.ai/free/en/papers/liang-2021-towards-understanding-mitigating-social-biases/)
212. [**Condenser: a Pre-training Architecture for Dense Retrieval**Luyu Gao, Jamie Callan*2021 · 261 citations*](https://md.research.elamur.ai/free/en/papers/gao-2021-condenser-pre-training-architecture-dense/)
213. [**Unicoder: A Universal Language Encoder by Pre-training with Multiple Cross-lingual Tasks**Haoyang Huang, Yaobo Liang, Nan Duan, et al.*2019 · 261 citations*](https://md.research.elamur.ai/free/en/papers/huang-2019-unicoder-universal-language-encoder-pre/)
214. [**SemEval-2020 Task 8: Memotion Analysis- the Visuo-Lingual Metaphor!**Chhavi Sharma, Deepesh Bhageria, William Scott, et al.*2020 · 260 citations*](https://md.research.elamur.ai/free/en/papers/sharma-2020-semeval-2020-task-8-memotion/)
215. [**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/)
216. [**How Can We Accelerate Progress Towards Human-like Linguistic Generalization?**Tal Linzen*2020 · 257 citations*](https://md.research.elamur.ai/free/en/papers/linzen-2020-how-can-we-accelerate-progress/)
217. [**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/)
218. [**An Empirical Survey of Data Augmentation for Limited Data Learning in NLP**Jiaao Chen, Derek Tam, Colin Raffel, et al.*2023 · 253 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-empirical-survey-data-augmentation-limited/)
219. [**CorefQA: Coreference Resolution as Query-based Span Prediction**Wei Wu, Fei Wang, Arianna Yuan, et al.*2020 · 253 citations*](https://md.research.elamur.ai/free/en/papers/wu-2020-corefqa-coreference-resolution-as-query/)
220. [**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/)
221. [**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/)
222. [**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/)
223. [**Event Extraction as Multi-turn Question Answering**Fayuan Li, Weihua Peng, Yuguang Chen, et al.*2020 · 250 citations*](https://md.research.elamur.ai/free/en/papers/li-2020-event-extraction-as-multi-turn/)
224. [**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/)
225. [**CLPsych 2019 Shared Task: Predicting the Degree of Suicide Risk in Reddit Posts**Ayah Zirikly, Philip Resnik, Özlem Uzuner, et al.*2019 · 246 citations*](https://md.research.elamur.ai/free/en/papers/zirikly-2019-clpsych-2019-shared-task-predicting/)
226. [**Perturbed Masking: Parameter-free Probing for Analyzing and Interpreting BERT**Zhiyong Wu, Yun Chen, Ben Kao, et al.*2020 · 244 citations*](https://md.research.elamur.ai/free/en/papers/wu-2020-perturbed-masking-parameter-free-probing/)
227. [**Unsupervised Domain Adaptation of Contextualized Embeddings for Sequence Labeling**Xiaochuang Han, Jacob Eisenstein*2019 · 242 citations*](https://md.research.elamur.ai/free/en/papers/han-2019-unsupervised-domain-adaptation-contextualized-embeddings/)
228. [**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/)
229. [**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/)
230. [**MTOP: A Comprehensive Multilingual Task-Oriented Semantic Parsing Benchmark**Haoran Li, Abhinav Arora, Shuohui Chen, et al.*2021 · 239 citations*](https://md.research.elamur.ai/free/en/papers/li-2021-mtop-comprehensive-multilingual-task-oriented/)
231. [**Analysing Lexical Semantic Change with Contextualised Word Representations**Mario Giulianelli, Marco Del Tredici, Raquel Fernández*2020 · 239 citations*](https://md.research.elamur.ai/free/en/papers/giulianelli-2020-analysing-lexical-semantic-change-contextualised/)
232. [**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/)
233. [**Knowledge Graph Based Synthetic Corpus Generation for Knowledge-Enhanced Language Model Pre-training**Oshin Agarwal, Heming Ge, Siamak Shakeri, et al.*2021 · 238 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2021-knowledge-graph-based-synthetic-corpus/)
234. [**MultiQA: An Empirical Investigation of Generalization and Transfer in Reading Comprehension**Alon Talmor, Jonathan Berant*2019 · 234 citations*](https://md.research.elamur.ai/free/en/papers/talmor-2019-multiqa-empirical-investigation-generalization-transfer/)
235. [**CONTaiNER: Few-Shot Named Entity Recognition via Contrastive Learning**Sarkar Snigdha Sarathi Das, Arzoo Katiyar, Rebecca Passonneau, et al.*2022 · 233 citations*](https://md.research.elamur.ai/free/en/papers/das-2022-container-few-shot-named-entity/)
236. [**Dialog State Tracking: A Neural Reading Comprehension Approach**Shuyang Gao, Abhishek Sethi, Sanchit Agarwal, et al.*2019 · 233 citations*](https://md.research.elamur.ai/free/en/papers/gao-2019-dialog-state-tracking-neural-reading/)
237. [**Breaking Through the 80% Glass Ceiling: Raising the State of the Art in Word Sense Disambiguation by Incorporating Knowledge Graph Information**Michele Bevilacqua, Roberto Navigli*2020 · 232 citations*](https://md.research.elamur.ai/free/en/papers/bevilacqua-2020-breaking-through-80-glass-ceiling/)
238. [**Moving Down the Long Tail of Word Sense Disambiguation with Gloss Informed Bi-encoders**Terra Blevins, Luke Zettlemoyer*2020 · 232 citations*](https://md.research.elamur.ai/free/en/papers/blevins-2020-moving-down-long-tail-word/)
239. [**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/)
240. [**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/)
241. [**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/)
242. [**Multilingual Translation from Denoising Pre-Training**Yuqing Tang, Chau Tran, Xian Li, et al.*2021 · 219 citations*](https://md.research.elamur.ai/free/en/papers/tang-2021-multilingual-translation-denoising-pre-training/)
243. [**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/)
244. [**What Happens To BERT Embeddings During Fine-tuning?**Amil Merchant, Elahe Rahimtoroghi, Ellie Pavlick, et al.*2020 · 219 citations*](https://md.research.elamur.ai/free/en/papers/merchant-2020-what-happens-bert-embeddings-during/)
245. [**Head-Driven Phrase Structure Grammar Parsing on Penn Treebank**Junru Zhou, Hai Zhao*2019 · 219 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2019-head-driven-phrase-structure-grammar/)
246. [**Real-Time Open-Domain Question Answering with Dense-Sparse Phrase Index**Minjoon Seo, Jinhyuk Lee, Tom Kwiatkowski, et al.*2019 · 216 citations*](https://md.research.elamur.ai/free/en/papers/seo-2019-real-time-open-domain-question/)
247. [**Syntactic Data Augmentation Increases Robustness to Inference Heuristics**Junghyun Min, R. Thomas McCoy, Dipanjan Das, et al.*2020 · 215 citations*](https://md.research.elamur.ai/free/en/papers/min-2020-syntactic-data-augmentation-increases-robustness/)
248. [**An Empirical Survey of the Effectiveness of Debiasing Techniques for Pre-trained Language Models**Nicholas Meade, Elinor Poole-Dayan, Siva Reddy*2022 · 211 citations*](https://md.research.elamur.ai/free/en/papers/meade-2022-empirical-survey-effectiveness-debiasing-techniques/)
249. [**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/)
250. [**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/)
251. [**Entities as Experts: Sparse Memory Access with Entity Supervision**Thibault Févry, Livio Baldini Soares, Nicholas FitzGerald, et al.*2020 · 205 citations*](https://md.research.elamur.ai/free/en/papers/fevry-2020-entities-as-experts-sparse-memory/)
252. [**Improved Lexically Constrained Decoding for Translation and Monolingual Rewriting**J. Edward Hu, Huda Khayrallah, Ryan Culkin, et al.*2019 · 198 citations*](https://md.research.elamur.ai/free/en/papers/hu-2019-improved-lexically-constrained-decoding-translation/)
253. [**Neural Metaphor Detection in Context**Ge Gao, Eunsol Choi, Yejin Choi, et al.*2018 · 198 citations*](https://md.research.elamur.ai/free/en/papers/gao-2018-neural-metaphor-detection-context/)
254. [**COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining**Yu Meng, Chenyan Xiong, Payal Bajaj, et al.*2021 · 196 citations*](https://md.research.elamur.ai/free/en/papers/meng-2021-coco-lm-correcting-contrasting-text/)
255. [**Structured Pruning of Large Language Models**Ziheng Wang, Jeremy Wohlwend, Tao Lei*2020 · 196 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-structured-pruning-large-language-models/)
256. [**Time-Aware Language Models as Temporal Knowledge Bases**Bhuwan Dhingra, Jeremy R. Cole, Julian Martin Eisenschlos, et al.*2022 · 194 citations*](https://md.research.elamur.ai/free/en/papers/dhingra-2022-time-aware-language-models-as/)
257. [**Exploring and Predicting Transferability across NLP Tasks**Tu Vu, Tong Wang, Tsendsuren Munkhdalai, et al.*2020 · 192 citations*](https://md.research.elamur.ai/free/en/papers/vu-2020-exploring-predicting-transferability-across-nlp/)
258. [**Merging Models with Fisher-Weighted Averaging**Michael Matena, Colin Raffel*2021 · 190 citations*](https://md.research.elamur.ai/free/en/papers/matena-2021-merging-models-fisher-weighted-averaging/)
259. [**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/)
260. [**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/)
261. [**A Survey on Stance Detection for Mis- and Disinformation Identification**Momchil Hardalov, Arnav Arora, Preslav Nakov, et al.*2022 · 187 citations*](https://md.research.elamur.ai/free/en/papers/hardalov-2022-survey-stance-detection-mis-disinformation/)
262. [**Modeling Intra and Inter-modality Incongruity for Multi-Modal Sarcasm Detection**Hongliang Pan, Zheng Lin, Peng Fu, et al.*2020 · 181 citations*](https://md.research.elamur.ai/free/en/papers/pan-2020-modeling-intra-inter-modality-incongruity/)
263. [**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/)
264. [**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/)
265. [**Massive Choice, Ample Tasks (MaChAmp): A Toolkit for Multi-task Learning in NLP**Rob van der Goot, Ahmet Üstün, Alan Ramponi, et al.*2021 · 177 citations*](https://md.research.elamur.ai/free/en/papers/goot-2021-massive-choice-ample-tasks-machamp/)
266. [**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/)
267. [**Multilingual LAMA: Investigating Knowledge in Multilingual Pretrained Language Models**Nora Kassner, Philipp Dufter, Hinrich Schütze*2021 · 175 citations*](https://md.research.elamur.ai/free/en/papers/kassner-2021-multilingual-lama-investigating-knowledge-multilingual/)
268. [**Neural Syntactic Preordering for Controlled Paraphrase Generation**Tanya Goyal, Greg Durrett*2020 · 167 citations*](https://md.research.elamur.ai/free/en/papers/goyal-2020-neural-syntactic-preordering-controlled-paraphrase/)
269. [**On Generative Spoken Language Modeling from Raw Audio**Kushal Lakhotia, Eugene Kharitonov, Wei-Ning Hsu, et al.*2021 · 165 citations*](https://md.research.elamur.ai/free/en/papers/lakhotia-2021-generative-spoken-language-modeling-raw/)
270. [**Sustainable Modular Debiasing of Language Models**Anne Lauscher, Tobias Lueken, Goran Glavaš*2021 · 165 citations*](https://md.research.elamur.ai/free/en/papers/lauscher-2021-sustainable-modular-debiasing-language-models/)
271. [**Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution**Shany Barhom, Vered Shwartz, Alon Eirew, et al.*2019 · 164 citations*](https://md.research.elamur.ai/free/en/papers/barhom-2019-revisiting-joint-modeling-cross-document/)
272. [**Probing What Different NLP Tasks Teach Machines about Function Word Comprehension**Najoung Kim, Roma Patel, Adam Poliak, et al.*2019 · 161 citations*](https://md.research.elamur.ai/free/en/papers/kim-2019-probing-what-different-nlp-tasks/)
273. [**Canine: Pre-training an Efficient Tokenization-Free Encoder for Language Representation**Jonathan H. Clark, Dan Garrette, Iulia Turc, et al.*2022 · 156 citations*](https://md.research.elamur.ai/free/en/papers/clark-2022-canine-pre-training-efficient-tokenization/)
274. [**Towards a Cleaner Document-Oriented Multilingual Crawled Corpus**Julien Abadji, Pedro Ortiz Suarez, Laurent Romary, et al.*2022 · 154 citations*](https://md.research.elamur.ai/free/en/papers/abadji-2022-towards-cleaner-document-oriented-multilingual/)
275. [**Efficient Second-Order TreeCRF for Neural Dependency Parsing**Yu Zhang, Zhenghua Li, Min Zhang*2020 · 145 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2020-efficient-second-order-treecrf-neural/)
276. [**Is GPT-3 a Good Data Annotator?**Bosheng Ding, Chengwei Qin, Linlin Liu, et al.*2022 · 144 citations*](https://md.research.elamur.ai/free/en/papers/ding-2022-gpt-3-good-data-annotator/)
277. [**Revealing the Myth of Higher-Order Inference in Coreference Resolution**Liyan Xu, Jinho D. Choi*2020 · 144 citations*](https://md.research.elamur.ai/free/en/papers/xu-2020-revealing-myth-higher-order-inference/)
278. [**UNQOVERing Stereotyping Biases via Underspecified Questions**Tao Li, Daniel Khashabi, Tushar Khot, et al.*2020 · 144 citations*](https://md.research.elamur.ai/free/en/papers/li-2020-unqovering-stereotyping-biases-underspecified-questions/)
279. [**Deep contextualized word representations for detecting sarcasm and irony**Suzana Ilić, Edison Marrese-Taylor, Jorge Balazs, et al.*2018 · 141 citations*](https://md.research.elamur.ai/free/en/papers/ilic-2018-deep-contextualized-word-representations-detecting/)
280. [**How does GPT-2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language model**Michael Hanna, Ollie Liu, Alexandre Variengien*2023 · 140 citations*](https://md.research.elamur.ai/free/en/papers/hanna-2023-gpt-2-compute-greater-than/)
281. [**Extending a Parser to Distant Domains Using a Few Dozen Partially Annotated Examples**Vidur Joshi, Matthew Peters, Mark Hopkins*2018 · 139 citations*](https://md.research.elamur.ai/free/en/papers/joshi-2018-extending-parser-distant-domains-few/)
282. [**Scaling up CometKiwi: Unbabel-IST 2023 Submission for the Quality Estimation Shared Task**Ricardo Rei, Nuno M. Guerreiro, José Pombal, et al.*2023 · 135 citations*](https://md.research.elamur.ai/free/en/papers/rei-2023-scaling-up-cometkiwi-unbabel-ist/)
283. [**Affective and Contextual Embedding for Sarcasm Detection**Nastaran Babanejad, Heidar Davoudi, Aijun An, et al.*2020 · 135 citations*](https://md.research.elamur.ai/free/en/papers/babanejad-2020-affective-contextual-embedding-sarcasm-detection/)
284. [**DisSent: Learning Sentence Representations from Explicit Discourse Relations**Allen Nie, Erin Bennett, Noah Goodman*2019 · 134 citations*](https://md.research.elamur.ai/free/en/papers/nie-2019-dissent-learning-sentence-representations-explicit/)
285. [**Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches**Shane Storks, Qiaozi Gao, Joyce Y. Chai*2019 · 134 citations*](https://md.research.elamur.ai/free/en/papers/storks-2019-recent-advances-natural-language-inference/)
286. [**Next Sentence Prediction helps Implicit Discourse Relation Classification within and across Domains**Wei Shi, Vera Demberg*2019 · 133 citations*](https://md.research.elamur.ai/free/en/papers/shi-2019-next-sentence-prediction-helps-implicit/)
287. [**Extracting Latent Steering Vectors from Pretrained Language Models**Nishant Subramani, Nivedita Suresh, Matthew Peters*2022 · 131 citations*](https://md.research.elamur.ai/free/en/papers/subramani-2022-extracting-latent-steering-vectors-pretrained/)
288. [**Deep Enhanced Representation for Implicit Discourse Relation Recognition**Hongxiao Bai, Hai Zhao*2018 · 131 citations*](https://md.research.elamur.ai/free/en/papers/bai-2018-deep-enhanced-representation-implicit-discourse/)
289. [**Learning Compact Metrics for MT**Amy Pu, Hyung Won Chung, Ankur Parikh, et al.*2021 · 130 citations*](https://md.research.elamur.ai/free/en/papers/pu-2021-learning-compact-metrics-mt/)
290. [**Still a Pain in the Neck: Evaluating Text Representations on Lexical Composition**Vered Shwartz, Ido Dagan*2019 · 129 citations*](https://md.research.elamur.ai/free/en/papers/shwartz-2019-still-pain-neck-evaluating-text/)
291. [**Interpretable Neural Predictions with Differentiable Binary Variables**Jasmijn Bastings, Wilker Aziz, Ivan Titov*2019 · 126 citations*](https://md.research.elamur.ai/free/en/papers/bastings-2019-interpretable-neural-predictions-differentiable-binary/)
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