---
title: "Artificial Intelligence — papers, page 4"
description: "Artificial Intelligence: 7,180 papers of the Elamur Research library · page 4 of 73 · 226–325, the most cited first — our summary of each, its ideas…"
canonical: "https://research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/page/4/"
---
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# 🤖 Artificial Intelligence

7,180 papers · page 4 of 73 · 226–325 · the most cited first · [all shelves](https://md.research.elamur.ai/free/en/shelves/)

Artificial Intelligence is a subfield of Computer Science in the OpenAlex classification of science. The topics most of its papers here are on: «Natural Language Processing Techniques», «Topic Modeling», «Speech and dialogue systems».

## Papers

[← prev](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/page/3/) [1](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) [2](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/page/2/) [3](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/page/3/) **4** [5](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/page/5/) … [73](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/page/73/) [next →](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/page/5/)

226. [**AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts**Taylor Shin, Yasaman Razeghi, Robert L. Logan IV, et al.*2020 · 1,879 citations*](https://md.research.elamur.ai/free/en/papers/shin-2020-autoprompt-eliciting-knowledge-language-models/)
227. [**Focal Loss for Dense Object Detection**Tsung-Yi Lin, Priya Goyal, Ross Girshick, et al.*2017 · 1,867 citations*](https://md.research.elamur.ai/free/en/papers/lin-2017-focal-loss-dense-object-detection/)
228. [**A Language Modeling Approach to Information Retrieval**Jay M. Ponte, W. Bruce Croft*1998 · 1,867 citations*](https://md.research.elamur.ai/free/en/papers/ponte-1998-language-modeling-approach-information/)
229. [**Microsoft COCO Captions: Data Collection and Evaluation Server**Xinlei Chen, Hao Fang, Tsung-Yi Lin, et al.*2015 · 1,859 citations*](https://md.research.elamur.ai/free/en/papers/chen-2015-microsoft-coco-captions-data-collection/)
230. [**Character-Aware Neural Language Models**Yoon Kim, Yacine Jernite, David Sontag, et al.*2015 · 1,852 citations*](https://md.research.elamur.ai/free/en/papers/kim-2015-character-aware-neural-language-models/)
231. [**Personalizing Dialogue Agents: I have a dog, do you have pets too?**Saizheng Zhang, Emily Dinan, Jack Urbanek, et al.*2018 · 1,839 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2018-personalizing-dialogue-agents-i-have/)
232. [**Automatically Constructing a Corpus of Sentential Paraphrases**William B. Dolan, Chris Brockett*2005 · 1,839 citations*](https://md.research.elamur.ai/free/en/papers/dolan-2005-automatically-constructing-corpus-sentential-paraphrases/)
233. [**Unsupervised Data Augmentation for Consistency Training**Qizhe Xie, Zihang Dai, Eduard Hovy, et al.*2019 · 1,837 citations*](https://md.research.elamur.ai/free/en/papers/xie-2019-unsupervised-data-augmentation-consistency-training/)
234. [**Design Challenges and Misconceptions in Named Entity Recognition**Lev Ratinov, Dan Roth*2009 · 1,836 citations*](https://md.research.elamur.ai/free/en/papers/ratinov-2009-design-challenges-misconceptions-named-entity/)
235. [**Scaling Laws for Neural Language Models**Jared Kaplan, Sam McCandlish, Tom Henighan, et al.*2020 · 1,814 citations*](https://md.research.elamur.ai/free/en/papers/kaplan-2020-scaling-laws-neural-language-models/)
236. [**PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization**Jingqing Zhang, Yao Zhao, Mohammad Saleh, et al.*2019 · 1,806 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2019-pegasus-pre-training-extracted-gap/)
237. [**AllenNLP: A Deep Semantic Natural Language Processing Platform**Matt Gardner, Joel Grus, Mark Neumann, et al.*2018 · 1,804 citations*](https://md.research.elamur.ai/free/en/papers/gardner-2018-allennlp-deep-semantic-natural-language/)
238. [**“Liar, Liar Pants on Fire”: A New Benchmark Dataset for Fake News Detection**William Yang Wang*2017 · 1,801 citations*](https://md.research.elamur.ai/free/en/papers/wang-2017-liar-liar-pants-fire-new/)
239. [**DeBERTa: Decoding-enhanced BERT with Disentangled Attention**Pengcheng He, Xiaodong Liu, Jianfeng Gao, et al.*2020 · 1,800 citations*](https://md.research.elamur.ai/free/en/papers/he-2020-deberta-decoding-enhanced-bert-disentangled/)
240. [**A Survey on Hate Speech Detection using Natural Language Processing**Anna Schmidt, Michael Wiegand*2017 · 1,799 citations*](https://md.research.elamur.ai/free/en/papers/schmidt-2017-survey-hate-speech-detection-natural/)
241. [**Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering**Michael Defferrard, Xavier Bresson, Pierre Vandergheynst*2016 · 1,797 citations*](https://md.research.elamur.ai/free/en/papers/defferrard-2016-convolutional-neural-networks-graphs-fast/)
242. [**Exploiting Cloze-Questions for Few-Shot Text Classification and Natural Language Inference**Timo Schick, Hinrich Schütze*2021 · 1,796 citations*](https://md.research.elamur.ai/free/en/papers/schick-2021-exploiting-cloze-questions-few-shot/)
243. [**The Penn Discourse TreeBank 2.0.**Rashmi Prasad, Nikhil Dinesh, Alan Lee, et al.*2008 · 1,793 citations*](https://md.research.elamur.ai/free/en/papers/prasad-2008-penn-discourse-treebank-2-0/)
244. [**Domain Adaptation with Structural Correspondence Learning**John Blitzer, Ryan McDonald, Fernando Pereira*2006 · 1,792 citations*](https://md.research.elamur.ai/free/en/papers/blitzer-2006-domain-adaptation-structural-correspondence-learning/)
245. [**What Does BERT Learn about the Structure of Language?**Ganesh Jawahar, Benoît Sagot, Djamé Seddah*2019 · 1,789 citations*](https://md.research.elamur.ai/free/en/papers/jawahar-2019-what-does-bert-learn-about/)
246. [**Towards Deep Learning Models Resistant to Adversarial Attacks**Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, et al.*2017 · 1,786 citations*](https://md.research.elamur.ai/free/en/papers/madry-2017-towards-deep-learning-models-resistant/)
247. [**COMET: A Neural Framework for MT Evaluation**Ricardo Rei, Craig Stewart, Ana C Farinha, et al.*2020 · 1,784 citations*](https://md.research.elamur.ai/free/en/papers/rei-2020-comet-neural-framework-mt-evaluation/)
248. [**ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT**Omar Khattab, Matei Zaharia*2020 · 1,776 citations*](https://md.research.elamur.ai/free/en/papers/khattab-2020-colbert-efficient-effective-passage/)
249. [**Attention-Based Models for Speech Recognition**Jan Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk, et al.*2015 · 1,776 citations*](https://md.research.elamur.ai/free/en/papers/chorowski-2015-attention-based-models-speech-recognition/)
250. [**Transformation-Based Error-Driven Learning and Natural Language Processing: A Case Study in Part-of-Speech Tagging**Eric Brill*1995 · 1,774 citations*](https://md.research.elamur.ai/free/en/papers/brill-1995-transformation-based-error-driven-learning/)
251. [**A Structured Self-attentive Sentence Embedding**Zhouhan Lin, Minwei Feng, Cicero Nogueira dos Santos, et al.*2017 · 1,773 citations*](https://md.research.elamur.ai/free/en/papers/lin-2017-structured-self-attentive-sentence-embedding/)
252. [**Survey Article: Inter-Coder Agreement for Computational Linguistics**Ron Artstein, Massimo Poesio*2008 · 1,770 citations*](https://md.research.elamur.ai/free/en/papers/artstein-2008-survey-article-inter-coder-agreement/)
253. [**A Neural Conversational Model**Oriol Vinyals, Quoc Le*2015 · 1,759 citations*](https://md.research.elamur.ai/free/en/papers/vinyals-2015-neural-conversational-model/)
254. [**KenLM: Faster and Smaller Language Model Queries**Kenneth Heafield*2011 · 1,759 citations*](https://md.research.elamur.ai/free/en/papers/heafield-2011-kenlm-faster-smaller-language-model/)
255. [**TnT – A Statistical Part-of-Speech Tagger**Thorsten Brants*2000 · 1,756 citations*](https://md.research.elamur.ai/free/en/papers/brants-2000-tnt-statistical-part-speech-tagger/)
256. [**Pre-trained Models for Natural Language Processing: A Survey**Xipeng Qiu, Tianxiang Sun, Yige Xu, et al.*2020 · 1,740 citations*](https://md.research.elamur.ai/free/en/papers/qiu-2020-pre-trained-models-natural-language/)
257. [**Universal Dependencies v1: A Multilingual Treebank Collection**Joakim Nivre, Marie-Catherine de Marneffe, Filip Ginter, et al.*2016 · 1,739 citations*](https://md.research.elamur.ai/free/en/papers/nivre-2016-universal-dependencies-v1-multilingual-treebank/)
258. [**Longformer: The Long-Document Transformer**Iz Beltagy, Matthew E. Peters, Arman Cohan*2020 · 1,737 citations*](https://md.research.elamur.ai/free/en/papers/beltagy-2020-longformer-long-document-transformer/)
259. [**BERTopic: Neural topic modeling with a class-based TF-IDF procedure**Maarten Grootendorst*2022 · 1,729 citations*](https://md.research.elamur.ai/free/en/papers/grootendorst-2022-bertopic-neural-topic-modeling-class/)
260. [**OPT: Open Pre-trained Transformer Language Models**Susan Zhang, Stephen Roller, Naman Goyal, et al.*2022 · 1,709 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2022-opt-open-pre-trained-transformer/)
261. [**Language (Technology) is Power: A Critical Survey of “Bias” in NLP**Su Lin Blodgett, Solon Barocas, Hal Daumé III, et al.*2020 · 1,700 citations*](https://md.research.elamur.ai/free/en/papers/blodgett-2020-language-technology-is-power-critical/)
262. [**Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models**Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.*2022 · 1,695 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2022-imitation-game-quantifying-extrapolating-capabilities/)
263. [**A Hierarchical Phrase-Based Model for Statistical Machine Translation**David Chiang*2005 · 1,683 citations*](https://md.research.elamur.ai/free/en/papers/chiang-2005-hierarchical-phrase-based-model-statistical/)
264. [**Don't count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors**Marco Baroni, Georgiana Dinu, Germán Kruszewski*2014 · 1,678 citations*](https://md.research.elamur.ai/free/en/papers/baroni-2014-don-t-count-predict-systematic/)
265. [**Determining the Sentiment of Opinions**Soo-Min Kim, Eduard Hovy*2004 · 1,677 citations*](https://md.research.elamur.ai/free/en/papers/kim-2004-determining-sentiment-opinions/)
266. [**Document Modeling with Gated Recurrent Neural Network for Sentiment Classification**Duyu Tang, Bing Qin, Ting Liu*2015 · 1,675 citations*](https://md.research.elamur.ai/free/en/papers/tang-2015-document-modeling-gated-recurrent-neural/)
267. [**Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering**Gautier Izacard, Edouard Grave*2021 · 1,674 citations*](https://md.research.elamur.ai/free/en/papers/izacard-2021-leveraging-passage-retrieval-generative-models/)
268. [**Pointer Sentinel Mixture Models**Stephen Merity, Caiming Xiong, James Bradbury, et al.*2016 · 1,669 citations*](https://md.research.elamur.ai/free/en/papers/merity-2016-pointer-sentinel-mixture-models/)
269. [**MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations**Soujanya Poria, Devamanyu Hazarika, Navonil Majumder, et al.*2018 · 1,668 citations*](https://md.research.elamur.ai/free/en/papers/poria-2018-meld-multimodal-multi-party-dataset/)
270. [**Relation Classification via Convolutional Deep Neural Network**Daojian Zeng, Kang Liu, Siwei Lai, et al.*2014 · 1,659 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2014-relation-classification-convolutional-deep-neural/)
271. [**SemEval-2016 Task 5: Aspect Based Sentiment Analysis**Maria Pontiki, Dimitris Galanis, Haris Papageorgiou, et al.*2016 · 1,656 citations*](https://md.research.elamur.ai/free/en/papers/pontiki-2016-semeval-2016-task-5-aspect/)
272. [**Retrieval-Augmented Generation for Large Language Models: A Survey**Yunfan Gao, Yun Xiong, Xinyu Gao, et al.*2023 · 1,647 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-retrieval-augmented-generation-large-language/)
273. [**Learning Question Classifiers**Xin Li, Dan Roth*2002 · 1,645 citations*](https://md.research.elamur.ai/free/en/papers/li-2002-learning-question-classifiers/)
274. [**Qwen Technical Report**Jinze Bai, Shuai Bai, Yunfei Chu, et al.*2023 · 1,643 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-qwen-technical-report/)
275. [**Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inference**R. Thomas McCoy, Ellie Pavlick, Tal Linzen*2019 · 1,630 citations*](https://md.research.elamur.ai/free/en/papers/mccoy-2019-right-wrong-reasons-diagnosing-syntactic/)
276. [**Hierarchical Phrase-Based Translation**David Chiang*2007 · 1,628 citations*](https://md.research.elamur.ai/free/en/papers/chiang-2007-hierarchical-phrase-based-translation/)
277. [**A Deep Reinforced Model for Abstractive Summarization**Romain Paulus, Caiming Xiong, Richard Socher*2017 · 1,626 citations*](https://md.research.elamur.ai/free/en/papers/paulus-2017-deep-reinforced-model-abstractive-summarization/)
278. [**SimLex-999: Evaluating Semantic Models With (Genuine) Similarity Estimation**Felix Hill, Roi Reichart, Anna Korhonen*2015 · 1,622 citations*](https://md.research.elamur.ai/free/en/papers/hill-2015-simlex-999-evaluating-semantic-models/)
279. [**RACE: Large-scale ReAding Comprehension Dataset From Examinations**Guokun Lai, Qizhe Xie, Hanxiao Liu, et al.*2017 · 1,619 citations*](https://md.research.elamur.ai/free/en/papers/lai-2017-race-large-scale-reading-comprehension/)
280. [**A Simple Rule-Based Part of Speech Tagger**Eric Brill*1992 · 1,618 citations*](https://md.research.elamur.ai/free/en/papers/brill-1992-simple-rule-based-part-speech/)
281. [**Universal Sentence Encoder**Daniel Cer, Yinfei Yang, Sheng-yi Kong, et al.*2018 · 1,616 citations*](https://md.research.elamur.ai/free/en/papers/cer-2018-universal-sentence-encoder/)
282. [**Evaluating WordNet-based Measures of Lexical Semantic Relatedness**Alexander Budanitsky, Graeme Hirst*2006 · 1,610 citations*](https://md.research.elamur.ai/free/en/papers/budanitsky-2006-evaluating-wordnet-based-measures-lexical/)
283. [**Recurrent Continuous Translation Models**Nal Kalchbrenner, Phil Blunsom*2013 · 1,597 citations*](https://md.research.elamur.ai/free/en/papers/kalchbrenner-2013-recurrent-continuous-translation-models/)
284. [**End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures**Makoto Miwa, Mohit Bansal*2016 · 1,596 citations*](https://md.research.elamur.ai/free/en/papers/miwa-2016-end-end-relation-extraction-lstms/)
285. [**A Decomposable Attention Model for Natural Language Inference**Ankur Parikh, Oscar Täckström, Dipanjan Das, et al.*2016 · 1,589 citations*](https://md.research.elamur.ai/free/en/papers/parikh-2016-decomposable-attention-model-natural-language/)
286. [**Deep Unsupervised Learning using Nonequilibrium Thermodynamics**Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, et al.*2015 · 1,588 citations*](https://md.research.elamur.ai/free/en/papers/sohl-dickstein-2015-deep-unsupervised-learning-using-nonequilibrium/)
287. [**Layer Normalization**Jimmy Lei Ba, Jamie Ryan Kiros, Geoffrey E. Hinton*2016 · 1,587 citations*](https://md.research.elamur.ai/free/en/papers/ba-2016-layer-normalization/)
288. [**Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task**Tao Yu, Rui Zhang, Kai Yang, et al.*2018 · 1,582 citations*](https://md.research.elamur.ai/free/en/papers/yu-2018-spider-large-scale-human-labeled/)
289. [**Multitask Prompted Training Enables Zero-Shot Task Generalization**Victor Sanh, Albert Webson, Colin Raffel, et al.*2021 · 1,577 citations*](https://md.research.elamur.ai/free/en/papers/sanh-2021-multitask-prompted-training-enables-zero/)
290. [**Deep Speech: Scaling up end-to-end speech recognition**Awni Hannun, Carl Case, Jared Casper, et al.*2014 · 1,575 citations*](https://md.research.elamur.ai/free/en/papers/hannun-2014-deep-speech-scaling-up-end/)
291. [**mT5: A Massively Multilingual Pre-trained Text-to-Text Transformer**Linting Xue, Noah Constant, Adam Roberts, et al.*2021 · 1,574 citations*](https://md.research.elamur.ai/free/en/papers/xue-2021-mt5-massively-multilingual-pre-trained/)
292. [**WordNet Affect: an Affective Extension of WordNet**Carlo Strapparava, Alessandro Valitutti*2004 · 1,573 citations*](https://md.research.elamur.ai/free/en/papers/strapparava-2004-wordnet-affect-affective-extension-wordnet/)
293. [**The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables**Chris J. Maddison, Andriy Mnih, Yee Whye Teh*2016 · 1,569 citations*](https://md.research.elamur.ai/free/en/papers/maddison-2016-concrete-distribution-continuous-relaxation-discrete/)
294. [**SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documents**Ramesh Nallapati, Feifei Zhai, Bowen Zhou*2016 · 1,566 citations*](https://md.research.elamur.ai/free/en/papers/nallapati-2016-summarunner-recurrent-neural-network-based/)
295. [**Semantic Compositionality through Recursive Matrix-Vector Spaces**Richard Socher, Brody Huval, Christopher D. Manning, et al.*2012 · 1,559 citations*](https://md.research.elamur.ai/free/en/papers/socher-2012-semantic-compositionality-through-recursive-matrix/)
296. [**A Maximum Entropy Model for Part-Of-Speech Tagging**Adwait Ratnaparkhi*1996 · 1,554 citations*](https://md.research.elamur.ai/free/en/papers/ratnaparkhi-1996-maximum-entropy-model-part-speech/)
297. [**Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey**Bonan Min, Hayley Ross, Elior Sulem, et al.*2021 · 1,548 citations*](https://md.research.elamur.ai/free/en/papers/min-2021-recent-advances-natural-language-processing/)
298. [**Unifying Large Language Models and Knowledge Graphs: A Roadmap**Shirui Pan, Linhao Luo, Yufei Wang, et al.*2023 · 1,545 citations*](https://md.research.elamur.ai/free/en/papers/pan-2023-unifying-large-language-models-knowledge/)
299. [**Universal Sentence Encoder for English**Daniel Cer, Yinfei Yang, Sheng-yi Kong, et al.*2018 · 1,544 citations*](https://md.research.elamur.ai/free/en/papers/cer-2018-universal-sentence-encoder-english/)
300. [**Competition-Level Code Generation with AlphaCode**Yujia Li, David Choi, Junyoung Chung, et al.*2022 · 1,543 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-competition-level-code-generation-alphacode/)
301. [**CoQA: A Conversational Question Answering Challenge**Siva Reddy, Danqi Chen, Christopher D. Manning*2019 · 1,541 citations*](https://md.research.elamur.ai/free/en/papers/reddy-2019-coqa-conversational-question-answering-challenge/)
302. [**ChatGPT Outperforms Crowd-Workers for Text-Annotation Tasks**Fabrizio Gilardi, Meysam Alizadeh, Maël Kubli*2023 · 1,532 citations*](https://md.research.elamur.ai/free/en/papers/gilardi-2023-chatgpt-outperforms-crowd-workers-text/)
303. [**Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision**Chao Jia, Yinfei Yang, Ye Xia, et al.*2021 · 1,528 citations*](https://md.research.elamur.ai/free/en/papers/jia-2021-scaling-up-visual-vision-language/)
304. [**Score-Based Generative Modeling through Stochastic Differential Equations**Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, et al.*2020 · 1,528 citations*](https://md.research.elamur.ai/free/en/papers/song-2020-score-based-generative-modeling-through/)
305. [**Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context**Gemini Team, Petko Georgiev, Ving Ian Lei, et al.*2024 · 1,522 citations*](https://md.research.elamur.ai/free/en/papers/gemini-team-2024-gemini-1-5-unlocking-multimodal/)
306. [**Efficient Transformers: A Survey**Yi Tay, Mostafa Dehghani, Dara Bahri, et al.*2020 · 1,513 citations*](https://md.research.elamur.ai/free/en/papers/tay-2020-efficient-transformers-survey/)
307. [**Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned**Elena Voita, David Talbot, Fedor Moiseev, et al.*2019 · 1,511 citations*](https://md.research.elamur.ai/free/en/papers/voita-2019-analyzing-multi-head-self-attention/)
308. [**VisualBERT: A Simple and Performant Baseline for Vision and Language**Liunian Harold Li, Mark Yatskar, Da Yin, et al.*2019 · 1,510 citations*](https://md.research.elamur.ai/free/en/papers/li-2019-visualbert-simple-performant-baseline-vision/)
309. [**Multimodal Language Analysis in the Wild: CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph**AmirAli Bagher Zadeh, Paul Pu Liang, Soujanya Poria, et al.*2018 · 1,506 citations*](https://md.research.elamur.ai/free/en/papers/zadeh-2018-multimodal-language-analysis-wild-cmu/)
310. [**Multi-Task Deep Neural Networks for Natural Language Understanding**Xiaodong Liu, Pengcheng He, Weizhu Chen, et al.*2019 · 1,501 citations*](https://md.research.elamur.ai/free/en/papers/liu-2019-multi-task-deep-neural-networks/)
311. [**CLIPScore: A Reference-free Evaluation Metric for Image Captioning**Jack Hessel, Ari Holtzman, Maxwell Forbes, et al.*2021 · 1,498 citations*](https://md.research.elamur.ai/free/en/papers/hessel-2021-clipscore-reference-free-evaluation-metric/)
312. [**Multiword Expressions: A Pain in the Neck for NLP**Ivan A. Sag, Timothy Baldwin, Francis Bond, et al.*2002 · 1,497 citations*](https://md.research.elamur.ai/free/en/papers/sag-2002-multiword-expressions-pain-neck-nlp/)
313. [**How Can We Know What Language Models Know?**Zhengbao Jiang, Frank F. Xu, Jun Araki, et al.*2020 · 1,493 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2020-how-can-we-know-what/)
314. [**The State and Fate of Linguistic Diversity and Inclusion in the NLP World**Pratik Joshi, Sebastin Santy, Amar Budhiraja, et al.*2020 · 1,492 citations*](https://md.research.elamur.ai/free/en/papers/joshi-2020-state-fate-linguistic-diversity-inclusion/)
315. [**LEGAL-BERT: The Muppets straight out of Law School**Ilias Chalkidis, Manos Fergadiotis, Prodromos Malakasiotis, et al.*2020 · 1,490 citations*](https://md.research.elamur.ai/free/en/papers/chalkidis-2020-legal-bert-muppets-straight-out/)
316. [**Automatic Word Sense Discrimination**Hinrich Schütze*1998 · 1,486 citations*](https://md.research.elamur.ai/free/en/papers/schutze-1998-automatic-word-sense-discrimination/)
317. [**Hedges: A Study in Meaning Criteria and the Logic of Fuzzy Concepts**George Lakoff*1973 · 1,486 citations*](https://md.research.elamur.ai/free/en/papers/lakoff-1973-hedges-study-meaning-criteria/)
318. [**Pre-Training with Whole Word Masking for Chinese BERT**Yiming Cui, Wanxiang Che, Ting Liu, et al.*2019 · 1,485 citations*](https://md.research.elamur.ai/free/en/papers/cui-2019-pre-training-whole-word-masking/)
319. [**Deep Reinforcement Learning for Dialogue Generation**Jiwei Li, Will Monroe, Alan Ritter, et al.*2016 · 1,479 citations*](https://md.research.elamur.ai/free/en/papers/li-2016-deep-reinforcement-learning-dialogue-generation/)
320. [**Understanding Black-box Predictions via Influence Functions**Pang Wei Koh, Percy Liang*2017 · 1,478 citations*](https://md.research.elamur.ai/free/en/papers/koh-2017-understanding-black-box-predictions-influence/)
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