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# Works of United States

2809 · page 2 of 29 · the most cited first · [← United States](https://md.research.elamur.ai/free/en/countries/united-states/)

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101. [**Robust Speech Recognition via Large-Scale Weak Supervision**Alec Radford, Jong Wook Kim, Tao Xu, et al.*2022 · 2,497 citations*](https://md.research.elamur.ai/free/en/papers/radford-2022-robust-speech-recognition-large-scale/)
102. [**ReAct: Synergizing Reasoning and Acting in Language Models**Shunyu Yao, Jeffrey Zhao, Dian Yu, et al.*2022 · 2,493 citations*](https://md.research.elamur.ai/free/en/papers/yao-2022-react-synergizing-reasoning-acting-language/)
103. [**Visual Instruction Tuning**Haotian Liu, Chunyuan Li, Qingyang Wu, et al.*2023 · 2,487 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-visual-instruction-tuning/)
104. [**OpenNMT: Open-Source Toolkit for Neural Machine Translation**Guillaume Klein, Yoon Kim, Yuntian Deng, et al.*2017 · 2,460 citations*](https://md.research.elamur.ai/free/en/papers/klein-2017-opennmt-open-source-toolkit-neural/)
105. [**Statistical Significance Tests for Machine Translation Evaluation**Philipp Koehn*2004 · 2,444 citations*](https://md.research.elamur.ai/free/en/papers/koehn-2004-statistical-significance-tests-machine-translation/)
106. [**Word Representations: A Simple and General Method for Semi-Supervised Learning**Joseph Turian, Lev-Arie Ratinov, Yoshua Bengio*2010 · 2,421 citations*](https://md.research.elamur.ai/free/en/papers/turian-2010-word-representations-simple-general-method/)
107. [**Meteor Universal: Language Specific Translation Evaluation for Any Target Language**Michael Denkowski, Alon Lavie*2014 · 2,392 citations*](https://md.research.elamur.ai/free/en/papers/denkowski-2014-meteor-universal-language-specific-translation/)
108. [**Sparks of Artificial General Intelligence: Early experiments with GPT-4**Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, et al.*2023 · 2,389 citations*](https://md.research.elamur.ai/free/en/papers/bubeck-2023-sparks-artificial-general-intelligence-early/)
109. [**Learning Important Features Through Propagating Activation Differences**Avanti Shrikumar, Peyton Greenside, Anshul Kundaje*2017 · 2,377 citations*](https://md.research.elamur.ai/free/en/papers/shrikumar-2017-learning-important-features-through-propagating/)
110. [**Generating Sentences from a Continuous Space**Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, et al.*2016 · 2,367 citations*](https://md.research.elamur.ai/free/en/papers/bowman-2016-generating-sentences-continuous-space/)
111. [**Self-critical Sequence Training for Image Captioning**Steven J. Rennie, Etienne Marcheret, Youssef Mroueh, et al.*2016 · 2,367 citations*](https://md.research.elamur.ai/free/en/papers/rennie-2016-self-critical-sequence-training-image/)
112. [**Stanza: A Python Natural Language Processing Toolkit for Many Human Languages**Peng Qi, Yuhao Zhang, Yuhui Zhang, et al.*2020 · 2,347 citations*](https://md.research.elamur.ai/free/en/papers/qi-2020-stanza-python-natural-language-processing/)
113. [**UNITER: UNiversal Image-TExt Representation Learning**Yen-Chun Chen, Linjie Li, Licheng Yu, et al.*2019 · 2,344 citations*](https://md.research.elamur.ai/free/en/papers/chen-2019-uniter-universal-image-text-representation/)
114. [**Measuring Mathematical Problem Solving With the MATH Dataset**Dan Hendrycks, Collin Burns, Saurav Kadavath, et al.*2021 · 2,318 citations*](https://md.research.elamur.ai/free/en/papers/hendrycks-2021-measuring-mathematical-problem-solving-math/)
115. [**A Fast and Accurate Dependency Parser using Neural Networks**Danqi Chen, Christopher Manning*2014 · 2,301 citations*](https://md.research.elamur.ai/free/en/papers/chen-2014-fast-accurate-dependency-parser-neural/)
116. [**Conceptual Captions: A Cleaned, Hypernymed, Image Alt-text Dataset For Automatic Image Captioning**Piyush Sharma, Nan Ding, Sebastian Goodman, et al.*2018 · 2,278 citations*](https://md.research.elamur.ai/free/en/papers/sharma-2018-conceptual-captions-cleaned-hypernymed-image/)
117. [**Reading Wikipedia to Answer Open-Domain Questions**Danqi Chen, Adam Fisch, Jason Weston, et al.*2017 · 2,250 citations*](https://md.research.elamur.ai/free/en/papers/chen-2017-reading-wikipedia-answer-open-domain/)
118. [**Equality of Opportunity in Supervised Learning**Moritz Hardt, Eric Price, Nathan Srebro*2016 · 2,224 citations*](https://md.research.elamur.ai/free/en/papers/hardt-2016-equality-opportunity-supervised-learning/)
119. [**Automatic Labeling of Semantic Roles**Daniel Gildea, Daniel Jurafsky*2002 · 2,216 citations*](https://md.research.elamur.ai/free/en/papers/gildea-2002-automatic-labeling-semantic-roles/)
120. [**Emergent Abilities of Large Language Models**Jason Wei, Yi Tay, Rishi Bommasani, et al.*2022 · 2,215 citations*](https://md.research.elamur.ai/free/en/papers/wei-2022-emergent-abilities-large-language-models/)
121. [**FEVER: a Large-scale Dataset for Fact Extraction and VERification**James Thorne, Andreas Vlachos, Christos Christodoulopoulos, et al.*2018 · 2,205 citations*](https://md.research.elamur.ai/free/en/papers/thorne-2018-fever-large-scale-dataset-fact/)
122. [**SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems**Alex Wang, Yada Pruksachatkun, Nikita Nangia, et al.*2019 · 2,187 citations*](https://md.research.elamur.ai/free/en/papers/wang-2019-superglue-stickier-benchmark-general-purpose/)
123. [**WordNet: A Lexical Database for English**George A. Miller*1994 · 2,179 citations*](https://md.research.elamur.ai/free/en/papers/miller-1994-wordnet/)
124. [**Multimodal Transformer for Unaligned Multimodal Language Sequences**Yao-Hung Hubert Tsai, Shaojie Bai, Paul Pu Liang, et al.*2019 · 2,170 citations*](https://md.research.elamur.ai/free/en/papers/tsai-2019-multimodal-transformer-unaligned-multimodal-language/)
125. [**Probabilistic Latent Semantic Analysis**Thomas Hofmann*1999 · 2,145 citations*](https://md.research.elamur.ai/free/en/papers/hofmann-1999-probabilistic-latent-semantic-analysis/)
126. [**A Primer in BERTology: What We Know About How BERT Works**Anna Rogers, Olga Kovaleva, Anna Rumshisky*2020 · 2,127 citations*](https://md.research.elamur.ai/free/en/papers/rogers-2020-primer-bertology-what-we-know/)
127. [**BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models**Junnan Li, Dongxu Li, Silvio Savarese, et al.*2023 · 2,114 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-blip-2-bootstrapping-language-image/)
128. [**Tensor Fusion Network for Multimodal Sentiment Analysis**Amir Zadeh, Minghai Chen, Soujanya Poria, et al.*2017 · 2,107 citations*](https://md.research.elamur.ai/free/en/papers/zadeh-2017-tensor-fusion-network-multimodal-sentiment/)
129. [**Centering: A Framework for Modeling the Local Coherence of Discourse**Barbara J. Grosz, Aravind K. Joshi, Scott Weinstein*1995 · 2,101 citations*](https://md.research.elamur.ai/free/en/papers/grosz-1995-centering-framework-modeling-local-coherence/)
130. [**How Multilingual is Multilingual BERT?**Telmo Pires, Eva Schlinger, Dan Garrette*2019 · 2,095 citations*](https://md.research.elamur.ai/free/en/papers/pires-2019-how-multilingual-is-multilingual-bert/)
131. [**A Maximum-Entropy-Inspired Parser**Eugene Charniak*2000 · 2,049 citations*](https://md.research.elamur.ai/free/en/papers/charniak-2000-maximum-entropy-inspired-parser/)
132. [**Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings**Tolga Bolukbasi, Kai-Wei Chang, James Zou, et al.*2016 · 2,038 citations*](https://md.research.elamur.ai/free/en/papers/bolukbasi-2016-man-computer-programmer-woman-homemaker/)
133. [**Reading Tea Leaves: How Humans Interpret Topic Models**Jonathan Chang, Jordan Boyd-Graber, Sean Gerrish, et al.*2009 · 2,037 citations*](https://md.research.elamur.ai/free/en/papers/chang-2009-reading-tea-leaves-humans-interpret-topic/)
134. [**Information structure in discourse: Towards an integrated formal theory of pragmatics**Craige Roberts*2012 · 2,020 citations*](https://md.research.elamur.ai/free/en/papers/roberts-2012-information-structure-discourse-towards-integrated/)
135. [**Knowledge Graphs**Aidan Hogan, Eva Blomqvist, Michael Cochez, et al.*2020 · 2,011 citations*](https://md.research.elamur.ai/free/en/papers/hogan-2020-knowledge-graphs/)
136. [**Head-Driven Statistical Models for Natural Language Parsing**Michael Collins*2003 · 2,001 citations*](https://md.research.elamur.ai/free/en/papers/collins-2003-head-driven-statistical-models-natural/)
137. [**GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering**Drew A. Hudson, Christopher D. Manning*2019 · 1,997 citations*](https://md.research.elamur.ai/free/en/papers/hudson-2019-gqa-new-dataset-real-world/)
138. [**BERT Rediscovers the Classical NLP Pipeline**Ian Tenney, Dipanjan Das, Ellie Pavlick*2019 · 1,993 citations*](https://md.research.elamur.ai/free/en/papers/tenney-2019-bert-rediscovers-classical-nlp-pipeline/)
139. [**MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems**Tianqi Chen, Mu Li, Yutian Li, et al.*2015 · 1,981 citations*](https://md.research.elamur.ai/free/en/papers/chen-2015-mxnet-flexible-efficient-machine-learning/)
140. [**Automatic Evaluation of Summaries Using N-gram Co-occurrence Statistics**Chin-Yew Lin, Eduard Hovy*2003 · 1,967 citations*](https://md.research.elamur.ai/free/en/papers/lin-2003-automatic-evaluation-summaries-n-gram/)
141. [**Making Pre-trained Language Models Better Few-shot Learners**Tianyu Gao, Adam Fisch, Danqi Chen*2021 · 1,952 citations*](https://md.research.elamur.ai/free/en/papers/gao-2021-making-pre-trained-language-models/)
142. [**Adversarial Examples for Evaluating Reading Comprehension Systems**Robin Jia, Percy Liang*2017 · 1,935 citations*](https://md.research.elamur.ai/free/en/papers/jia-2017-adversarial-examples-evaluating-reading-comprehension/)
143. [**Abstract Meaning Representation for Sembanking**Laura Banarescu, Claire Bonial, Shu Cai, et al.*2013 · 1,915 citations*](https://md.research.elamur.ai/free/en/papers/banarescu-2013-abstract-meaning-representation-sembanking/)
144. [**Extracting Product Features and Opinions from Reviews**Ana-Maria Popescu, Oren Etzioni*2005 · 1,904 citations*](https://md.research.elamur.ai/free/en/papers/popescu-2005-extracting-product-features-opinions-reviews/)
145. [**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/)
146. [**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/)
147. [**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/)
148. [**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/)
149. [**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/)
150. [**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/)
151. [**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/)
152. [**Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks**Xiujun Li, Xi Yin, Chunyuan Li, et al.*2020 · 1,827 citations*](https://md.research.elamur.ai/free/en/papers/li-2020-oscar-object-semantics-aligned-pre/)
153. [**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/)
154. [**“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/)
155. [**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/)
156. [**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/)
157. [**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/)
158. [**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/)
159. [**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/)
160. [**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/)
161. [**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/)
162. [**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/)
163. [**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/)
164. [**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/)
165. [**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/)
166. [**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/)
167. [**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/)
168. [**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/)
169. [**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/)
170. [**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/)
171. [**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/)
172. [**Learning Question Classifiers**Xin Li, Dan Roth*2002 · 1,645 citations*](https://md.research.elamur.ai/free/en/papers/li-2002-learning-question-classifiers/)
173. [**Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding**Akira Fukui, Dong Huk Park, Daylen Yang, et al.*2016 · 1,642 citations*](https://md.research.elamur.ai/free/en/papers/fukui-2016-multimodal-compact-bilinear-pooling-visual/)
174. [**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/)
175. [**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/)
176. [**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/)
177. [**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/)
178. [**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/)
179. [**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/)
180. [**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/)
181. [**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/)
182. [**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/)
183. [**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/)
184. [**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/)
185. [**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/)
186. [**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/)
187. [**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/)
188. [**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/)
189. [**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/)
190. [**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/)
191. [**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/)
192. [**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/)
193. [**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/)
194. [**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/)
195. [**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/)
196. [**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/)
197. [**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/)
198. [**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/)
199. [**Automatic Word Sense Discrimination**Hinrich Schütze*1998 · 1,486 citations*](https://md.research.elamur.ai/free/en/papers/schutze-1998-automatic-word-sense-discrimination/)
200. [**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/)

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