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# Works of United States

2809 · page 5 of 29 · the most cited first · [← United States](https://md.research.elamur.ai/free/en/countries/united-states/)

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401. [**Addressing the Rare Word Problem in Neural Machine Translation**Thang Luong, Ilya Sutskever, Quoc Le, et al.*2015 · 817 citations*](https://md.research.elamur.ai/free/en/papers/luong-2015-addressing-rare-word-problem-neural/)
402. [**ImageNet Large Scale Visual Recognition Challenge**Olga Russakovsky, Jia Deng, Hao Su, et al.*2014 · 816 citations*](https://md.research.elamur.ai/free/en/papers/russakovsky-2014-imagenet-large-scale-visual-recognition/)
403. [**Scaling Neural Machine Translation**Myle Ott, Sergey Edunov, David Grangier, et al.*2018 · 813 citations*](https://md.research.elamur.ai/free/en/papers/ott-2018-scaling-neural-machine-translation/)
404. [**Finding Deceptive Opinion Spam by Any Stretch of the Imagination**Myle Ott, Yejin Choi, Claire Cardie, et al.*2011 · 806 citations*](https://md.research.elamur.ai/free/en/papers/ott-2011-finding-deceptive-opinion-spam-any/)
405. [**Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond**Jingfeng Yang, Hongye Jin, Ruixiang Tang, et al.*2023 · 806 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-harnessing-power-llms-practice-survey/)
406. [**BARTScore: Evaluating Generated Text as Text Generation**Weizhe Yuan, Graham Neubig, Pengfei Liu*2021 · 806 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2021-bartscore-evaluating-generated-text-text/)
407. [**Calibrate Before Use: Improving Few-Shot Performance of Language Models**Tony Z. Zhao, Eric Wallace, Shi Feng, et al.*2021 · 791 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2021-calibrate-before-use-improving-few/)
408. [**ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission**Kexin Huang, Jaan Altosaar, Rajesh Ranganath*2019 · 788 citations*](https://md.research.elamur.ai/free/en/papers/huang-2019-clinicalbert-modeling-clinical-notes-predicting/)
409. [**From TreeBank to PropBank**Paul Kingsbury, Martha Palmer*2002 · 787 citations*](https://md.research.elamur.ai/free/en/papers/kingsbury-2002-treebank-propbank/)
410. [**Semi-supervised sequence tagging with bidirectional language models**Matthew E. Peters, Waleed Ammar, Chandra Bhagavatula, et al.*2017 · 786 citations*](https://md.research.elamur.ai/free/en/papers/peters-2017-semi-supervised-sequence-tagging-bidirectional/)
411. [**Scaling to Very Very Large Corpora for Natural Language Disambiguation**Michele Banko, Eric Brill*2001 · 785 citations*](https://md.research.elamur.ai/free/en/papers/banko-2001-scaling-very-very-large-corpora/)
412. [**Explainability for Large Language Models: A Survey**Haiyan Zhao, Hanjie Chen, Fan Yang, et al.*2023 · 785 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-explainability-large-language-models-survey/)
413. [**SemEval-2014 Task 10: Multilingual Semantic Textual Similarity**Eneko Agirre, Carmen Banea, Claire Cardie, et al.*2014 · 783 citations*](https://md.research.elamur.ai/free/en/papers/agirre-2014-semeval-2014-task-10-multilingual/)
414. [**Word-Sense Disambiguation Using Statistical Models of Roget's Categories Trained on Large Corpora**David Yarowsky*1992 · 782 citations*](https://md.research.elamur.ai/free/en/papers/yarowsky-1992-word-sense-disambiguation-statistical-models/)
415. [**Newsroom: A Dataset of 1.3 Million Summaries with Diverse Extractive Strategies**Max Grusky, Mor Naaman, Yoav Artzi*2018 · 778 citations*](https://md.research.elamur.ai/free/en/papers/grusky-2018-newsroom-dataset-1-3-million/)
416. [**Supervised Learning of Universal Sentence Representations from Natural Language Inference Data**Alexis Conneau, Douwe Kiela, Holger Schwenk, et al.*2017 · 777 citations*](https://md.research.elamur.ai/free/en/papers/conneau-2017-supervised-learning-universal-sentence-representations/)
417. [**Can Large Language Models Transform Computational Social Science?**Caleb Ziems, William Held, Omar Shaikh, et al.*2023 · 776 citations*](https://md.research.elamur.ai/free/en/papers/ziems-2023-large-language-models-transform-computational/)
418. [**Towards Reasoning in Large Language Models: A Survey**Jie Huang, Kevin Chen-Chuan Chang*2023 · 775 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-reasoning-large-language-models-survey/)
419. [**Ask Me Anything: Dynamic Memory Networks for Natural Language Processing**Ankit Kumar, Ozan Irsoy, Peter Ondruska, et al.*2015 · 775 citations*](https://md.research.elamur.ai/free/en/papers/kumar-2015-ask-me-anything-dynamic-memory/)
420. [**Reformer: The Efficient Transformer**Nikita Kitaev, Łukasz Kaiser, Anselm Levskaya*2020 · 774 citations*](https://md.research.elamur.ai/free/en/papers/kitaev-2020-reformer-efficient-transformer/)
421. [**Domain Adaptation via Pseudo In-Domain Data Selection**Amittai Axelrod, Xiaodong He, Jianfeng Gao*2011 · 773 citations*](https://md.research.elamur.ai/free/en/papers/axelrod-2011-domain-adaptation-pseudo-domain-data/)
422. [**A Syntactic Neural Model for General-Purpose Code Generation**Pengcheng Yin, Graham Neubig*2017 · 772 citations*](https://md.research.elamur.ai/free/en/papers/yin-2017-syntactic-neural-model-general-purpose/)
423. [**Part-of-Speech Tagging for Twitter: Annotation, Features, and Experiments**Kevin Gimpel, Nathan Schneider, Brendan O'Connor, et al.*2011 · 767 citations*](https://md.research.elamur.ai/free/en/papers/gimpel-2011-part-speech-tagging-twitter-annotation/)
424. [**Non-Autoregressive Neural Machine Translation**Jiatao Gu, James Bradbury, Caiming Xiong, et al.*2017 · 765 citations*](https://md.research.elamur.ai/free/en/papers/gu-2017-non-autoregressive-neural-machine-translation/)
425. [**Rumor has it: Identifying Misinformation in Microblogs**Vahed Qazvinian, Emily Rosengren, Dragomir R. Radev, et al.*2011 · 764 citations*](https://md.research.elamur.ai/free/en/papers/qazvinian-2011-rumor-has-it-identifying-misinformation/)
426. [**On Measuring Social Biases in Sentence Encoders**Chandler May, Alex Wang, Shikha Bordia, et al.*2019 · 761 citations*](https://md.research.elamur.ai/free/en/papers/may-2019-measuring-social-biases-sentence-encoders/)
427. [**Colorless Green Recurrent Networks Dream Hierarchically**Kristina Gulordava, Piotr Bojanowski, Edouard Grave, et al.*2018 · 759 citations*](https://md.research.elamur.ai/free/en/papers/gulordava-2018-colorless-green-recurrent-networks-dream/)
428. [**Constituency Parsing with a Self-Attentive Encoder**Nikita Kitaev, Dan Klein*2018 · 759 citations*](https://md.research.elamur.ai/free/en/papers/kitaev-2018-constituency-parsing-self-attentive-encoder/)
429. [**SemEval-2015 Task 2: Semantic Textual Similarity, English, Spanish and Pilot on Interpretability**Eneko Agirre, Carmen Banea, Claire Cardie, et al.*2015 · 758 citations*](https://md.research.elamur.ai/free/en/papers/agirre-2015-semeval-2015-task-2-semantic/)
430. [**Learning Distributed Representations of Sentences from Unlabelled Data**Felix Hill, Kyunghyun Cho, Anna Korhonen*2016 · 756 citations*](https://md.research.elamur.ai/free/en/papers/hill-2016-learning-distributed-representations-sentences-unlabelled/)
431. [**Sarcasm as Contrast between a Positive Sentiment and Negative Situation**Ellen Riloff, Ashequl Qadir, Prafulla Surve, et al.*2013 · 752 citations*](https://md.research.elamur.ai/free/en/papers/riloff-2013-sarcasm-as-contrast-between-positive/)
432. [**The Woman Worked as a Babysitter: On Biases in Language Generation**Emily Sheng, Kai-Wei Chang, Premkumar Natarajan, et al.*2019 · 751 citations*](https://md.research.elamur.ai/free/en/papers/sheng-2019-woman-worked-as-babysitter-biases/)
433. [**Reproducible scaling laws for contrastive language-image learning**Mehdi Cherti, Romain Beaumont, Ross Wightman, et al.*2022 · 750 citations*](https://md.research.elamur.ai/free/en/papers/cherti-2022-reproducible-scaling-laws-contrastive-language/)
434. [**EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks**Jason Wei, Kai Zou*2019 · 750 citations*](https://md.research.elamur.ai/free/en/papers/wei-2019-eda-easy-data-augmentation-techniques/)
435. [**A Practical Part-of-Speech Tagger**Doug Cutting, Julian Kupiec, Jan Pedersen, et al.*1992 · 749 citations*](https://md.research.elamur.ai/free/en/papers/cutting-1992-practical-part-speech-tagger/)
436. [**Universal Dependency Annotation for Multilingual Parsing**Ryan McDonald, Joakim Nivre, Yvonne Quirmbach-Brundage, et al.*2013 · 749 citations*](https://md.research.elamur.ai/free/en/papers/mcdonald-2013-universal-dependency-annotation-multilingual-parsing/)
437. [**Findings of the 2018 Conference on Machine Translation (WMT18)**Ondřej Bojar, Christian Federmann, Mark Fishel, et al.*2018 · 747 citations*](https://md.research.elamur.ai/free/en/papers/bojar-2018-findings-2018-conference-machine-translation/)
438. [**Towards Faithfully Interpretable NLP Systems: How Should We Define and Evaluate Faithfulness?**Alon Jacovi, Yoav Goldberg*2020 · 747 citations*](https://md.research.elamur.ai/free/en/papers/jacovi-2020-faithfully-interpretable-nlp-systems-how/)
439. [**AdapterHub: A Framework for Adapting Transformers**Jonas Pfeiffer, Andreas Rücklé, Clifton Poth, et al.*2020 · 747 citations*](https://md.research.elamur.ai/free/en/papers/pfeiffer-2020-adapterhub-framework-adapting-transformers/)
440. [**Unified Pre-training for Program Understanding and Generation**Wasi Ahmad, Saikat Chakraborty, Baishakhi Ray, et al.*2021 · 746 citations*](https://md.research.elamur.ai/free/en/papers/ahmad-2021-unified-pre-training-program-understanding/)
441. [**Identifying Sarcasm in Twitter: A Closer Look**Roberto González-Ibáñez, Smaranda Muresan, Nina Wacholder*2011 · 742 citations*](https://md.research.elamur.ai/free/en/papers/ibanez-2011-identifying-sarcasm-twitter-closer-look/)
442. [**Integrating Multimodal Information in Large Pretrained Transformers**Wasifur Rahman, Md Kamrul Hasan, Sangwu Lee, et al.*2020 · 742 citations*](https://md.research.elamur.ai/free/en/papers/rahman-2020-integrating-multimodal-information-large-pretrained/)
443. [**SemEval-2014 Task 9: Sentiment Analysis in Twitter**Sara Rosenthal, Alan Ritter, Preslav Nakov, et al.*2014 · 741 citations*](https://md.research.elamur.ai/free/en/papers/rosenthal-2014-semeval-2014-task-9-sentiment/)
444. [**SentEval: An Evaluation Toolkit for Universal Sentence Representations**Alexis Conneau, Douwe Kiela*2018 · 739 citations*](https://md.research.elamur.ai/free/en/papers/conneau-2018-senteval-evaluation-toolkit-universal-sentence/)
445. [**Multi-News: A Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Model**Alexander Fabbri, Irene Li, Tianwei She, et al.*2019 · 738 citations*](https://md.research.elamur.ai/free/en/papers/fabbri-2019-multi-news-large-scale-multi/)
446. [**Revealing the Dark Secrets of BERT**Olga Kovaleva, Alexey Romanov, Anna Rogers, et al.*2019 · 737 citations*](https://md.research.elamur.ai/free/en/papers/kovaleva-2019-revealing-dark-secrets-bert/)
447. [**Resolving Pronoun References**Jerry R. Hobbs*1978 · 736 citations*](https://md.research.elamur.ai/free/en/papers/hobbs-1978-resolving-pronoun-references/)
448. [**Analysis Methods in Neural Language Processing: A Survey**Yonatan Belinkov, James Glass*2019 · 735 citations*](https://md.research.elamur.ai/free/en/papers/belinkov-2019-analysis-methods-neural-language-processing/)
449. [**MLQA: Evaluating Cross-lingual Extractive Question Answering**Patrick Lewis, Barlas Oğuz, Ruty Rinott, et al.*2019 · 735 citations*](https://md.research.elamur.ai/free/en/papers/lewis-2019-mlqa-evaluating-cross-lingual-extractive/)
450. [**Inducing Multilingual Text Analysis Tools via Robust Projection across Aligned Corpora**David Yarowsky, Grace Ngai, Richard Wicentowski*2001 · 734 citations*](https://md.research.elamur.ai/free/en/papers/yarowsky-2001-inducing-multilingual-text-analysis-tools/)
451. [**Common Voice: A Massively-Multilingual Speech Corpus**Rosana Ardila, Megan Branson, Kelly Davis, et al.*2019 · 733 citations*](https://md.research.elamur.ai/free/en/papers/ardila-2019-common-voice-massively-multilingual-speech/)
452. [**CIDEr: Consensus-based Image Description Evaluation**Ramakrishna Vedantam, C. Lawrence Zitnick, Devi Parikh*2014 · 733 citations*](https://md.research.elamur.ai/free/en/papers/vedantam-2014-cider-consensus-based-image-description/)
453. [**A Novel Cascade Binary Tagging Framework for Relational Triple Extraction**Zhepei Wei, Jianlin Su, Yue Wang, et al.*2020 · 732 citations*](https://md.research.elamur.ai/free/en/papers/wei-2020-novel-cascade-binary-tagging-framework/)
454. [**Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach**Wenpeng Yin, Jamaal Hay, Dan Roth*2019 · 731 citations*](https://md.research.elamur.ai/free/en/papers/yin-2019-benchmarking-zero-shot-text-classification/)
455. [**Online Learning of Approximate Dependency Parsing Algorithms**Ryan McDonald, Fernando Pereira*2006 · 729 citations*](https://md.research.elamur.ai/free/en/papers/mcdonald-2006-online-learning-approximate-dependency-parsing/)
456. [**A Joint Model of Text and Aspect Ratings for Sentiment Summarization**Ivan Titov, Ryan McDonald*2008 · 729 citations*](https://md.research.elamur.ai/free/en/papers/titov-2008-joint-model-text-aspect-ratings/)
457. [**The CoNLL 2008 Shared Task on Joint Parsing of Syntactic and Semantic Dependencies**Mihai Surdeanu, Richard Johansson, Adam Meyers, et al.*2008 · 728 citations*](https://md.research.elamur.ai/free/en/papers/surdeanu-2008-conll-2008-shared-task-joint/)
458. [**Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations**Philippe Tillet, H. T. Kung, David Cox*2019 · 728 citations*](https://md.research.elamur.ai/free/en/papers/tillet-2019-triton-intermediate-language-compiler-tiled/)
459. [**SoundStream: An End-to-End Neural Audio Codec**Neil Zeghidour, Alejandro Luebs, Ahmed Omran, et al.*2021 · 727 citations*](https://md.research.elamur.ai/free/en/papers/zeghidour-2021-soundstream-end-end-neural-audio/)
460. [**ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks**Mohit Shridhar; Jesse Thomason; Daniel Gordon; Yonatan Bisk; Winson Han; Roozbeh Mottaghi; Luke Zettlemoyer;, Dieter Fox*2019 · 724 citations*](https://md.research.elamur.ai/free/en/papers/shridhar-2019-alfred-benchmark-interpreting-grounded-instructions/)
461. [**Mitigating Gender Bias in Natural Language Processing: Literature Review**Tony Sun, Andrew Gaut, Shirlyn Tang, et al.*2019 · 716 citations*](https://md.research.elamur.ai/free/en/papers/sun-2019-mitigating-gender-bias-natural-language/)
462. [**Explainable Prediction of Medical Codes from Clinical Text**James Mullenbach, Sarah Wiegreffe, Jon Duke, et al.*2018 · 715 citations*](https://md.research.elamur.ai/free/en/papers/mullenbach-2018-explainable-prediction-medical-codes-clinical/)
463. [**Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions**Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, et al.*2022 · 711 citations*](https://md.research.elamur.ai/free/en/papers/trivedi-2022-interleaving-retrieval-chain-thought-reasoning/)
464. [**ProgPrompt: Generating Situated Robot Task Plans using Large Language Models**Ishika Singh, Valts Blukis, Arsalan Mousavian, et al.*2022 · 710 citations*](https://md.research.elamur.ai/free/en/papers/singh-2022-progprompt-generating-situated-robot-task/)
465. [**Scalable Modified Kneser-Ney Language Model Estimation**Kenneth Heafield, Ivan Pouzyrevsky, Jonathan H. Clark, et al.*2013 · 709 citations*](https://md.research.elamur.ai/free/en/papers/heafield-2013-scalable-modified-kneser-ney-language/)
466. [**A Multiscale Visualization of Attention in the Transformer Model**Jesse Vig*2019 · 708 citations*](https://md.research.elamur.ai/free/en/papers/vig-2019-multiscale-visualization-attention-transformer-model/)
467. [**Fact or Fiction: Verifying Scientific Claims**David Wadden, Shanchuan Lin, Kyle Lo, et al.*2020 · 706 citations*](https://md.research.elamur.ai/free/en/papers/wadden-2020-fact-or-fiction-verifying-scientific/)
468. [**The Web as a Parallel Corpus**Philip Resnik, Noah A. Smith*2003 · 703 citations*](https://md.research.elamur.ai/free/en/papers/resnik-2003-web-as-parallel-corpus/)
469. [**Large Language Models in Machine Translation**Thorsten Brants, Ashok C. Popat, Peng Xu, et al.*2007 · 701 citations*](https://md.research.elamur.ai/free/en/papers/brants-2007-large-language-models-machine-translation/)
470. [**Style Transfer in Text: Exploration and Evaluation**Zhenxin Fu, Xiaoye Tan, Nanyun Peng, et al.*2017 · 701 citations*](https://md.research.elamur.ai/free/en/papers/fu-2017-style-transfer-text-exploration-evaluation/)
471. [**Entity-Based Cross-Document Coreferencing Using the Vector Space Model**Amit Bagga, Breck Baldwin*1998 · 699 citations*](https://md.research.elamur.ai/free/en/papers/bagga-1998-entity-based-cross-document-coreferencing/)
472. [**Machine Reading Tea Leaves: Automatically Evaluating Topic Coherence and Topic Model Quality**Jey Han Lau, David Newman, Timothy Baldwin*2014 · 699 citations*](https://md.research.elamur.ai/free/en/papers/lau-2014-machine-reading-tea-leaves-automatically/)
473. [**Neural Text Generation from Structured Data with Application to the Biography Domain**Remi Lebret, David Grangier, Michael Auli*2016 · 696 citations*](https://md.research.elamur.ai/free/en/papers/lebret-2016-neural-text-generation-structured-data/)
474. [**The Goldilocks Principle: Reading Children's Books with Explicit Memory Representations**Felix Hill, Antoine Bordes, Sumit Chopra, et al.*2015 · 693 citations*](https://md.research.elamur.ai/free/en/papers/hill-2015-goldilocks-principle-reading-children-s/)
475. [**Crosslingual Generalization through Multitask Finetuning**Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.*2022 · 692 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-crosslingual-generalization-through-multitask-finetuning/)
476. [**Data-Driven Response Generation in Social Media**Alan Ritter, Colin Cherry, William B. Dolan*2011 · 692 citations*](https://md.research.elamur.ai/free/en/papers/ritter-2011-data-driven-response-generation-social/)
477. [**Extracting Paraphrases from a Parallel Corpus**Regina Barzilay, Kathleen R. McKeown*2001 · 691 citations*](https://md.research.elamur.ai/free/en/papers/barzilay-2001-extracting-paraphrases-parallel-corpus/)
478. [**TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages**Jonathan H. Clark, Eunsol Choi, Michael Collins, et al.*2020 · 691 citations*](https://md.research.elamur.ai/free/en/papers/clark-2020-tydi-qa-benchmark-information-seeking/)
479. [**GLTR: Statistical Detection and Visualization of Generated Text**Sebastian Gehrmann, Hendrik Strobelt, Alexander M. Rush*2019 · 691 citations*](https://md.research.elamur.ai/free/en/papers/gehrmann-2019-gltr-statistical-detection-visualization-generated/)
480. [**SPECTER: Document-level Representation Learning using Citation-informed Transformers**Arman Cohan, Sergey Feldman, Iz Beltagy, et al.*2020 · 690 citations*](https://md.research.elamur.ai/free/en/papers/cohan-2020-specter-document-level-representation-learning/)
481. [**Explain Yourself! Leveraging Language Models for Commonsense Reasoning**Nazneen Fatema Rajani, Bryan McCann, Caiming Xiong, et al.*2019 · 690 citations*](https://md.research.elamur.ai/free/en/papers/rajani-2019-explain-yourself-leveraging-language-models/)
482. [**TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data**Pengcheng Yin, Graham Neubig, Wen-tau Yih, et al.*2020 · 690 citations*](https://md.research.elamur.ai/free/en/papers/yin-2020-tabert-pretraining-joint-understanding-textual/)
483. [**A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task**Danqi Chen, Jason Bolton, Christopher D. Manning*2016 · 689 citations*](https://md.research.elamur.ai/free/en/papers/chen-2016-thorough-examination-cnn-daily-mail/)
484. [**Automatic Chain of Thought Prompting in Large Language Models**Zhuosheng Zhang, Aston Zhang, Mu Li, et al.*2022 · 688 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2022-automatic-chain-thought-prompting-large/)
485. [**Findings of the 2017 Conference on Machine Translation (WMT17)**Ondřej Bojar, Rajen Chatterjee, Christian Federmann, et al.*2017 · 685 citations*](https://md.research.elamur.ai/free/en/papers/bojar-2017-findings-2017-conference-machine-translation/)
486. [**CORD-19: The COVID-19 Open Research Dataset**Lucy Lu Wang, Kyle Lo, Yoganand Chandrasekhar, et al.*2020 · 685 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-cord-19-covid-19-open/)
487. [**Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes**Cheng-Yu Hsieh, Chun-Liang Li, Chih-kuan Yeh, et al.*2023 · 684 citations*](https://md.research.elamur.ai/free/en/papers/hsieh-2023-distilling-step-step-outperforming-larger/)
488. [**DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation**Yizhe Zhang, Siqi Sun, Michel Galley, et al.*2019 · 684 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2019-dialogpt-large-scale-generative-pre/)
489. [**A Class of Submodular Functions for Document Summarization**Hui Lin, Jeff Bilmes*2011 · 683 citations*](https://md.research.elamur.ai/free/en/papers/lin-2011-class-submodular-functions-document-summarization/)
490. [**ELI5: Long Form Question Answering**Angela Fan, Yacine Jernite, Ethan Perez, et al.*2019 · 682 citations*](https://md.research.elamur.ai/free/en/papers/fan-2019-eli5-long-form-question-answering/)
491. [**Semantic Parsing via Paraphrasing**Jonathan Berant, Percy Liang*2014 · 681 citations*](https://md.research.elamur.ai/free/en/papers/berant-2014-semantic-parsing-paraphrasing/)
492. [**Joint Event Extraction via Structured Prediction with Global Features**Qi Li, Heng Ji, Liang Huang*2013 · 681 citations*](https://md.research.elamur.ai/free/en/papers/li-2013-joint-event-extraction-structured-prediction/)
493. [**Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval**Lee Xiong, Chenyan Xiong, Ye Li, et al.*2020 · 681 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2020-approximate-nearest-neighbor-negative-contrastive/)
494. [**Espresso: Leveraging Generic Patterns for Automatically Harvesting Semantic Relations**Patrick Pantel, Marco Pennacchiotti*2006 · 680 citations*](https://md.research.elamur.ai/free/en/papers/pantel-2006-espresso-leveraging-generic-patterns-automatically/)
495. [**Social Bias Frames: Reasoning about Social and Power Implications of Language**Maarten Sap, Saadia Gabriel, Lianhui Qin, et al.*2020 · 680 citations*](https://md.research.elamur.ai/free/en/papers/sap-2020-social-bias-frames-reasoning-about/)
496. [**Bilingual Word Embeddings for Phrase-Based Machine Translation**Will Y. Zou, Richard Socher, Daniel Cer, et al.*2013 · 680 citations*](https://md.research.elamur.ai/free/en/papers/zou-2013-bilingual-word-embeddings-phrase-based/)
497. [**Globally Normalized Transition-Based Neural Networks**Daniel Andor, Chris Alberti, David Weiss, et al.*2016 · 676 citations*](https://md.research.elamur.ai/free/en/papers/andor-2016-globally-normalized-transition-based-neural/)
498. [**Mask-Predict: Parallel Decoding of Conditional Masked Language Models**Marjan Ghazvininejad, Omer Levy, Yinhan Liu, et al.*2019 · 671 citations*](https://md.research.elamur.ai/free/en/papers/ghazvininejad-2019-mask-predict-parallel-decoding-conditional/)
499. [**Well-Read Students Learn Better: On the Importance of Pre-training Compact Models**Iulia Turc, Ming-Wei Chang, Kenton Lee, et al.*2019 · 671 citations*](https://md.research.elamur.ai/free/en/papers/turc-2019-well-read-students-learn-better/)
500. [**Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences**Daniel Khashabi, Snigdha Chaturvedi, Michael Roth, et al.*2018 · 669 citations*](https://md.research.elamur.ai/free/en/papers/khashabi-2018-looking-beyond-surface-challenge-set/)

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