---
title: "Arts and Humanities — papers, page 6"
description: "Arts and Humanities: 7,418 papers of the Elamur Research library · page 6 of 75 · 426–525, the most cited first — our summary of each, its ideas…"
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# 🎭 Arts and Humanities

7,418 papers · page 6 of 75 · 426–525 · the most cited first · [all shelves](https://md.research.elamur.ai/free/en/shelves/)

Languages and linguistics, history, philosophy, literature, religion, music and the arts.

## Papers

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426. [**Visualizing and Understanding Recurrent Networks**Andrej Karpathy, Justin Johnson, Li Fei-Fei*2015 · 939 citations*](https://md.research.elamur.ai/free/en/papers/karpathy-2015-visualizing-understanding-recurrent-networks/)
427. [**Exploring Various Knowledge in Relation Extraction**GuoDong Zhou, Jian Su, Jie Zhang, et al.*2005 · 937 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2005-exploring-various-knowledge-relation-extraction/)
428. [**Automatic Evaluation of Machine Translation Quality Using Longest Common Subsequence and Skip-Bigram Statistics**Chin-Yew Lin, Franz Josef Och*2004 · 937 citations*](https://md.research.elamur.ai/free/en/papers/lin-2004-automatic-evaluation-machine-translation-quality/)
429. [**Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models**Yiheng Liu, Tianle Han, Siyuan Ma, et al.*2023 · 936 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-summary-chatgpt-related-research-perspective/)
430. [**Adversarial Example Generation with Syntactically Controlled Paraphrase Networks**Mohit Iyyer, John Wieting, Kevin Gimpel, et al.*2018 · 936 citations*](https://md.research.elamur.ai/free/en/papers/iyyer-2018-adversarial-example-generation-syntactically-controlled/)
431. [**Findings of the 2016 Conference on Machine Translation**Ondřej Bojar, Rajen Chatterjee, Christian Federmann, et al.*2016 · 936 citations*](https://md.research.elamur.ai/free/en/papers/bojar-2016-findings-2016-conference-machine-translation/)
432. [**A Survey of Data Augmentation Approaches for NLP**Steven Y. Feng, Varun Gangal, Jason Wei, et al.*2021 · 935 citations*](https://md.research.elamur.ai/free/en/papers/feng-2021-survey-data-augmentation-approaches-nlp/)
433. [**Multi-Task Identification of Entities, Relations, and Coreference for Scientific Knowledge Graph Construction**Yi Luan, Luheng He, Mari Ostendorf, et al.*2018 · 933 citations*](https://md.research.elamur.ai/free/en/papers/luan-2018-multi-task-identification-entities-relations/)
434. [**Rationalizing Neural Predictions**Tao Lei, Regina Barzilay, Tommi Jaakkola*2016 · 928 citations*](https://md.research.elamur.ai/free/en/papers/lei-2016-rationalizing-neural-predictions/)
435. [**Modeling Coverage for Neural Machine Translation**Zhaopeng Tu, Zhengdong Lu, Yang Liu, et al.*2016 · 927 citations*](https://md.research.elamur.ai/free/en/papers/tu-2016-modeling-coverage-neural-machine-translation/)
436. [**Collecting Highly Parallel Data for Paraphrase Evaluation**David Chen, William Dolan*2011 · 926 citations*](https://md.research.elamur.ai/free/en/papers/chen-2011-collecting-highly-parallel-data-paraphrase/)
437. [**Adapted Large Language Models Can Outperform Medical Experts in Clinical Text Summarization**Dave Van Veen, Cara Van Uden, Louis Blankemeier, et al.*2023 · 925 citations*](https://md.research.elamur.ai/free/en/papers/veen-2023-adapted-large-language-models-outperform/)
438. [**Bilateral Multi-Perspective Matching for Natural Language Sentences**Zhiguo Wang, Wael Hamza, Radu Florian*2017 · 923 citations*](https://md.research.elamur.ai/free/en/papers/wang-2017-bilateral-multi-perspective-matching-natural/)
439. [**Findings of the 2014 Workshop on Statistical Machine Translation**Ondřej Bojar, Christian Buck, Christian Federmann, et al.*2014 · 923 citations*](https://md.research.elamur.ai/free/en/papers/bojar-2014-findings-2014-workshop-statistical-machine/)
440. [**Improving Machine Learning Approaches to Coreference Resolution**Vincent Ng, Claire Cardie*2002 · 923 citations*](https://md.research.elamur.ai/free/en/papers/ng-2002-improving-machine-learning-approaches-coreference/)
441. [**Leveraging Linguistic Structure For Open Domain Information Extraction**Gabor Angeli, Melvin Jose Johnson Premkumar, Christopher D. Manning*2015 · 921 citations*](https://md.research.elamur.ai/free/en/papers/angeli-2015-leveraging-linguistic-structure-open-domain/)
442. [**C-Pack: Packed Resources For General Chinese Embeddings**Shitao Xiao, Zheng Liu, Peitian Zhang, et al.*2023 · 920 citations*](https://md.research.elamur.ai/free/en/papers/xiao-2023-c-pack-packed-resources/)
443. [**Clause Restructuring for Statistical Machine Translation**Michael Collins, Philipp Koehn, Ivona Kučerová*2005 · 918 citations*](https://md.research.elamur.ai/free/en/papers/collins-2005-clause-restructuring-statistical-machine-translation/)
444. [**Topic Modeling in Embedding Spaces**Adji B. Dieng, Francisco J. R. Ruiz, David M. Blei*2020 · 914 citations*](https://md.research.elamur.ai/free/en/papers/dieng-2020-topic-modeling-embedding-spaces/)
445. [**Deep Unordered Composition Rivals Syntactic Methods for Text Classification**Mohit Iyyer, Varun Manjunatha, Jordan Boyd-Graber, et al.*2015 · 914 citations*](https://md.research.elamur.ai/free/en/papers/iyyer-2015-deep-unordered-composition-rivals-syntactic/)
446. [**Learning to Ask: Neural Question Generation for Reading Comprehension**Xinya Du, Junru Shao, Claire Cardie*2017 · 913 citations*](https://md.research.elamur.ai/free/en/papers/du-2017-learning-ask-neural-question-generation/)
447. [**Modeling Local Coherence: An Entity-Based Approach**Regina Barzilay, Mirella Lapata*2008 · 912 citations*](https://md.research.elamur.ai/free/en/papers/barzilay-2008-modeling-local-coherence-entity-based/)
448. [**Building a Discourse-Tagged Corpus in the Framework of Rhetorical Structure Theory**Lynn Carlson, Daniel Marcu, Mary Ellen Okurovsky*2001 · 912 citations*](https://md.research.elamur.ai/free/en/papers/carlson-2001-building-discourse-tagged-corpus-framework/)
449. [**Universal Dependencies**Marie-Catherine de Marneffe, Christopher D. Manning, Joakim Nivre, et al.*2021 · 910 citations*](https://md.research.elamur.ai/free/en/papers/marneffe-2021-universal-dependencies-2/)
450. [**Grounded Compositional Semantics for Finding and Describing Images with Sentences**Richard Socher, Andrej Karpathy, Quoc V. Le, et al.*2014 · 909 citations*](https://md.research.elamur.ai/free/en/papers/socher-2014-grounded-compositional-semantics-finding-describing/)
451. [**Applying Conditional Random Fields to Japanese Morphological Analysis**Taku Kudo, Kaoru Yamamoto, Yuji Matsumoto*2004 · 909 citations*](https://md.research.elamur.ai/free/en/papers/kudo-2004-applying-conditional-random-fields-japanese/)
452. [**Three New Probabilistic Models for Dependency Parsing: An Exploration**Jason M. Eisner*1996 · 908 citations*](https://md.research.elamur.ai/free/en/papers/eisner-1996-three-new-probabilistic-models-dependency/)
453. [**SemEval-2017 Task 1: Semantic Textual Similarity Multilingual and Crosslingual Focused Evaluation**Daniel Cer, Mona Diab, Eneko Agirre, et al.*2017 · 907 citations*](https://md.research.elamur.ai/free/en/papers/cer-2017-semeval-2017-task-1-semantic/)
454. [**Dependency-Based Construction of Semantic Space Models**Sebastian Padó, Mirella Lapata*2007 · 906 citations*](https://md.research.elamur.ai/free/en/papers/pado-2007-dependency-based-construction-semantic-space/)
455. [**Representing Text for Joint Embedding of Text and Knowledge Bases**Kristina Toutanova, Danqi Chen, Patrick Pantel, et al.*2015 · 904 citations*](https://md.research.elamur.ai/free/en/papers/toutanova-2015-representing-text-joint-embedding-text/)
456. [**Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations**Eliyahu Kiperwasser, Yoav Goldberg*2016 · 903 citations*](https://md.research.elamur.ai/free/en/papers/kiperwasser-2016-simple-accurate-dependency-parsing-bidirectional/)
457. [**Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme**Suncong Zheng, Feng Wang, Hongyun Bao, et al.*2017 · 902 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2017-joint-extraction-entities-relations-based/)
458. [**Extracting Training Data from Large Language Models**Nicholas Carlini, Florian Tramer, Eric Wallace, et al.*2020 · 901 citations*](https://md.research.elamur.ai/free/en/papers/carlini-2020-extracting-training-data-large-language/)
459. [**A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT**Jules White, Quchen Fu, Sam Hays, et al.*2023 · 899 citations*](https://md.research.elamur.ai/free/en/papers/white-2023-prompt-pattern-catalog-enhance-prompt/)
460. [**Introduction to the CoNLL-2005 Shared Task: Semantic Role Labeling**Xavier Carreras, Lluís Màrquez*2005 · 899 citations*](https://md.research.elamur.ai/free/en/papers/carreras-2005-introduction-conll-2005-shared-task/)
461. [**Using the Output Embedding to Improve Language Models**Ofir Press, Lior Wolf*2017 · 891 citations*](https://md.research.elamur.ai/free/en/papers/press-2017-output-embedding-improve-language-models/)
462. [**LayoutLM: Pre-training of Text and Layout for Document Image Understanding**Yiheng Xu, Minghao Li, Lei Cui, et al.*2019 · 889 citations*](https://md.research.elamur.ai/free/en/papers/xu-2019-layoutlm-pre-training-text-layout/)
463. [**CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models**Nikita Nangia, Clara Vania, Rasika Bhalerao, et al.*2020 · 886 citations*](https://md.research.elamur.ai/free/en/papers/nangia-2020-crows-pairs-challenge-dataset-measuring/)
464. [**Is Attention Interpretable?**Sofia Serrano, Noah A. Smith*2019 · 885 citations*](https://md.research.elamur.ai/free/en/papers/serrano-2019-is-attention-interpretable/)
465. [**Generating Natural Language Adversarial Examples through Probability Weighted Word Saliency**Shuhuai Ren, Yihe Deng, Kun He, et al.*2019 · 884 citations*](https://md.research.elamur.ai/free/en/papers/ren-2019-generating-natural-language-adversarial-examples/)
466. [**Are NLP Models really able to Solve Simple Math Word Problems?**Arkil Patel, Satwik Bhattamishra, Navin Goyal*2021 · 882 citations*](https://md.research.elamur.ai/free/en/papers/patel-2021-are-nlp-models-really-able/)
467. [**Joint Event Extraction via Recurrent Neural Networks**Thien Huu Nguyen, Kyunghyun Cho, Ralph Grishman*2016 · 881 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2016-joint-event-extraction-recurrent-neural/)
468. [**Distributional Memory: A General Framework for Corpus-Based Semantics**Marco Baroni, Alessandro Lenci*2010 · 879 citations*](https://md.research.elamur.ai/free/en/papers/baroni-2010-distributional-memory-general-framework-corpus/)
469. [**Statistical Dependency Analysis with Support Vector Machines**Hiroyasu Yamada, Yuji Matsumoto*2003 · 878 citations*](https://md.research.elamur.ai/free/en/papers/yamada-2003-statistical-dependency-analysis-support-vector/)
470. [**MCTest: A Challenge Dataset for the Open-Domain Machine Comprehension of Text**Matthew Richardson, Christopher J.C. Burges, Erin Renshaw*2013 · 873 citations*](https://md.research.elamur.ai/free/en/papers/richardson-2013-mctest-challenge-dataset-open-domain/)
471. [**Instance Weighting for Domain Adaptation in NLP**Jing Jiang, ChengXiang Zhai*2007 · 870 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2007-instance-weighting-domain-adaptation-nlp/)
472. [**A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity**Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, et al.*2023 · 866 citations*](https://md.research.elamur.ai/free/en/papers/bang-2023-multitask-multilingual-multimodal-evaluation-chatgpt/)
473. [**ChatGPT: Jack of all trades, master of none**Jan Kocon, Igor Cichecki, Oliwier Kaszyca, et al.*2023 · 863 citations*](https://md.research.elamur.ai/free/en/papers/kocon-2023-chatgpt-jack-all-trades-master/)
474. [**Learning Subjective Language**Janyce Wiebe, Theresa Wilson, Rebecca Bruce, et al.*2004 · 861 citations*](https://md.research.elamur.ai/free/en/papers/wiebe-2004-learning-subjective-language/)
475. [**TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP**John X. Morris, Eli Lifland, Jin Yong Yoo, et al.*2020 · 857 citations*](https://md.research.elamur.ai/free/en/papers/morris-2020-textattack-framework-adversarial-attacks-data/)
476. [**Transition-Based Dependency Parsing with Stack Long Short-Term Memory**Chris Dyer, Miguel Ballesteros, Wang Ling, et al.*2015 · 857 citations*](https://md.research.elamur.ai/free/en/papers/dyer-2015-transition-based-dependency-parsing-stack/)
477. [**Nymble: a High-Performance Learning Name-finder**Daniel M. Bikel, Scott Miller, Richard Schwartz, et al.*1997 · 857 citations*](https://md.research.elamur.ai/free/en/papers/bikel-1997-nymble-high-performance-learning-name/)
478. [**On Coreference Resolution Performance Metrics**Xiaoqiang Luo*2005 · 855 citations*](https://md.research.elamur.ai/free/en/papers/luo-2005-coreference-resolution-performance-metrics/)
479. [**Gender Bias in Coreference Resolution**Rachel Rudinger, Jason Naradowsky, Brian Leonard, et al.*2018 · 852 citations*](https://md.research.elamur.ai/free/en/papers/rudinger-2018-gender-bias-coreference-resolution/)
480. [**End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF**Xuezhe Ma, Eduard Hovy*2016 · 852 citations*](https://md.research.elamur.ai/free/en/papers/ma-2016-end-end-sequence-labeling-bi/)
481. [**DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation**Deepanway Ghosal, Navonil Majumder, Soujanya Poria, et al.*2019 · 850 citations*](https://md.research.elamur.ai/free/en/papers/ghosal-2019-dialoguegcn-graph-convolutional-neural-network/)
482. [**TAGME: On-the-fly Annotation of Short Text Fragments (by Wikipedia Entities)**Paolo Ferragina, Ugo Scaiella*2010 · 849 citations*](https://md.research.elamur.ai/free/en/papers/ferragina-2010-tagme-fly-annotation-short/)
483. [**Intelligent Selection of Language Model Training Data**Robert C. Moore, William Lewis*2010 · 848 citations*](https://md.research.elamur.ai/free/en/papers/moore-2010-intelligent-selection-language-model-training/)
484. [**A robust self-learning method for fully unsupervised cross-lingual mappings of word embeddings**Mikel Artetxe, Gorka Labaka, Eneko Agirre*2018 · 847 citations*](https://md.research.elamur.ai/free/en/papers/artetxe-2018-vecmap-unsupervised/)
485. [**Challenges in Data-to-Document Generation**Sam Wiseman, Stuart M. Shieber, Alexander M. Rush*2017 · 846 citations*](https://md.research.elamur.ai/free/en/papers/wiseman-2017-challenges-data-document-generation/)
486. [**Effective Self-Training for Parsing**David McClosky, Eugene Charniak, Mark Johnson*2006 · 846 citations*](https://md.research.elamur.ai/free/en/papers/mcclosky-2006-effective-self-training-parsing/)
487. [**TaPas: Weakly Supervised Table Parsing via Pre-training**Jonathan Herzig, Pawel Krzysztof Nowak, Thomas Müller, et al.*2020 · 844 citations*](https://md.research.elamur.ai/free/en/papers/herzig-2020-tapas-weakly-supervised-table-parsing/)
488. [**UNIFIEDQA: Crossing Format Boundaries with a Single QA System**Daniel Khashabi, Sewon Min, Tushar Khot, et al.*2020 · 843 citations*](https://md.research.elamur.ai/free/en/papers/khashabi-2020-unifiedqa-crossing-format-boundaries-single/)
489. [**What BERT Is Not: Lessons from a New Suite of Psycholinguistic Diagnostics for Language Models**Allyson Ettinger*2020 · 843 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2020-what-bert-is-not-lessons/)
490. [**Visualizing and Understanding Neural Models in NLP**Jiwei Li, Xinlei Chen, Eduard Hovy, et al.*2016 · 842 citations*](https://md.research.elamur.ai/free/en/papers/li-2016-visualizing-understanding-neural-models-nlp/)
491. [**BERT-ATTACK: Adversarial Attack Against BERT Using BERT**Linyang Li, Ruotian Ma, Qipeng Guo, et al.*2020 · 840 citations*](https://md.research.elamur.ai/free/en/papers/li-2020-bert-attack-adversarial-attack-against/)
492. [**Unsupervised Learning of Sentence Embeddings Using Compositional n-Gram Features**Matteo Pagliardini, Prakhar Gupta, Martin Jaggi*2018 · 840 citations*](https://md.research.elamur.ai/free/en/papers/pagliardini-2018-unsupervised-learning-sentence-embeddings-compositional/)
493. [**Findings of the 2019 Conference on Machine Translation (WMT19)**Loïc Barrault, Ondřej Bojar, Marta R. Costa-jussà, et al.*2019 · 839 citations*](https://md.research.elamur.ai/free/en/papers/barrault-2019-findings-2019-conference-machine-translation/)
494. [**MADAMIRA: A Fast, Comprehensive Tool for Morphological Analysis and Disambiguation of Arabic**Arfath Pasha, Mohamed Al-Badrashiny, Mona Diab, et al.*2014 · 835 citations*](https://md.research.elamur.ai/free/en/papers/pasha-2014-madamira-fast-comprehensive-tool-morphological/)
495. [**A Unified MRC Framework for Named Entity Recognition**Xiaoya Li, Jingrong Feng, Yuxian Meng, et al.*2020 · 833 citations*](https://md.research.elamur.ai/free/en/papers/li-2020-unified-mrc-framework-named-entity/)
496. [**MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer**Jonas Pfeiffer, Ivan Vulić, Iryna Gurevych, et al.*2020 · 831 citations*](https://md.research.elamur.ai/free/en/papers/pfeiffer-2020-mad-x-adapter-based-framework/)
497. [**On the Sentence Embeddings from Pre-trained Language Models**Bohan Li, Hao Zhou, Junxian He, et al.*2020 · 830 citations*](https://md.research.elamur.ai/free/en/papers/li-2020-sentence-embeddings-pre-trained-language/)
498. [**Kernel Methods for Relation Extraction**Dmitry Zelenko, Chinatsu Aone, Anthony Richardella*2002 · 829 citations*](https://md.research.elamur.ai/free/en/papers/zelenko-2002-kernel-methods-relation-extraction/)
499. [**Unsupervised Dense Information Retrieval with Contrastive Learning**Gautier Izacard, Mathilde Caron, Lucas Hosseini, et al.*2021 · 824 citations*](https://md.research.elamur.ai/free/en/papers/izacard-2021-unsupervised-dense-information-retrieval-contrastive/)
500. [**A Convolutional Neural Network for Modelling Sentences**Nal Kalchbrenner, Edward Grefenstette, Phil Blunsom*2014 · 824 citations*](https://md.research.elamur.ai/free/en/papers/kalchbrenner-2014-convolutional-neural-network-modelling-sentences/)
501. [**Gated Self-Matching Networks for Reading Comprehension and Question Answering**Wenhui Wang, Nan Yang, Furu Wei, et al.*2017 · 823 citations*](https://md.research.elamur.ai/free/en/papers/wang-2017-gated-self-matching-networks-reading/)
502. [**Automatic Evaluation of Topic Coherence**David Newman, Jey Han Lau, Karl Grieser, et al.*2010 · 823 citations*](https://md.research.elamur.ai/free/en/papers/newman-2010-automatic-evaluation-topic-coherence/)
503. [**MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distance**Wei Zhao, Maxime Peyrard, Fei Liu, et al.*2019 · 822 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2019-moverscore-text-generation-evaluating-contextualized/)
504. [**Extended Gloss Overlaps as a Measure of Semantic Relatedness**Satanjeev Banerjee, Ted Pedersen*2003 · 822 citations*](https://md.research.elamur.ai/free/en/papers/banerjee-2003-extended-gloss-overlaps-as-measure/)
505. [**Multi-Way, Multilingual Neural Machine Translation with a Shared Attention Mechanism**Orhan Firat, Kyunghyun Cho, Yoshua Bengio*2016 · 821 citations*](https://md.research.elamur.ai/free/en/papers/firat-2016-multi-way-multilingual-neural-machine/)
506. [**Paraphrasing with Bilingual Parallel Corpora**Colin Bannard, Chris Callison-Burch*2005 · 821 citations*](https://md.research.elamur.ai/free/en/papers/bannard-2005-paraphrasing-bilingual-parallel-corpora/)
507. [**DocVQA: A Dataset for VQA on Document Images**Minesh Mathew, Dimosthenis Karatzas, C.V. Jawahar*2020 · 820 citations*](https://md.research.elamur.ai/free/en/papers/mathew-2020-docvqa-dataset-vqa-document-images/)
508. [**ERASER: A Benchmark to Evaluate Rationalized NLP Models**Jay DeYoung, Sarthak Jain, Nazneen Fatema Rajani, et al.*2020 · 820 citations*](https://md.research.elamur.ai/free/en/papers/deyoung-2020-eraser-benchmark-evaluate-rationalized-nlp/)
509. [**SemEval-2016 Task 1: Semantic Textual Similarity, Monolingual and Cross-Lingual Evaluation**Eneko Agirre, Carmen Banea, Daniel Cer, et al.*2016 · 820 citations*](https://md.research.elamur.ai/free/en/papers/agirre-2016-semeval-2016-task-1-semantic/)
510. [**Fast Abstractive Summarization with Reinforce-Selected Sentence Rewriting**Yen-Chun Chen, Mohit Bansal*2018 · 819 citations*](https://md.research.elamur.ai/free/en/papers/chen-2018-fast-abstractive-summarization-reinforce-selected/)
511. [**Improving Vector Space Word Representations Using Multilingual Correlation**Manaal Faruqui, Chris Dyer*2014 · 819 citations*](https://md.research.elamur.ai/free/en/papers/faruqui-2014-improving-vector-space-word-representations/)
512. [**Is ChatGPT a General-Purpose Natural Language Processing Task Solver?**Chengwei Qin, Aston Zhang, Zhuosheng Zhang, et al.*2023 · 818 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-chatgpt-general-purpose-natural-language/)
513. [**GPT-NeoX-20B: An Open-Source Autoregressive Language Model**Sidney Black, Stella Biderman, Eric Hallahan, et al.*2022 · 818 citations*](https://md.research.elamur.ai/free/en/papers/black-2022-gpt-neox-20b-open-source/)
514. [**Entity, Relation, and Event Extraction with Contextualized Span Representations**David Wadden, Ulme Wennberg, Yi Luan, et al.*2019 · 818 citations*](https://md.research.elamur.ai/free/en/papers/wadden-2019-entity-relation-event-extraction-contextualized/)
515. [**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/)
516. [**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/)
517. [**A New Dataset and Method for Automatically Grading ESOL Texts**Helen Yannakoudakis, Ted Briscoe, Ben Medlock*2011 · 813 citations*](https://md.research.elamur.ai/free/en/papers/yannakoudakis-2011-new-dataset-method-automatically-grading/)
518. [**Tokenizing, POS Tagging, Lemmatizing and Parsing UD 2.0 with UDPipe**Milan Straka, Jana Straková*2017 · 811 citations*](https://md.research.elamur.ai/free/en/papers/straka-2017-tokenizing-pos-tagging-lemmatizing-parsing/)
519. [**A Stylometric Inquiry into Hyperpartisan and Fake News**Martin Potthast, Johannes Kiesel, Kevin Reinartz, et al.*2018 · 808 citations*](https://md.research.elamur.ai/free/en/papers/potthast-2018-stylometric-inquiry-into-hyperpartisan-fake/)
520. [**Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks**Chen Zhang, Qiuchi Li, Dawei Song*2019 · 807 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2019-aspect-based-sentiment-classification-aspect/)
521. [**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/)
522. [**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/)
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