--- title: "Natural language processing — papers, page 15" description: "Natural language processing: 2421 papers of the Elamur Research library · page 15 of 97 — our summary of each, its ideas, references and who cites it." canonical: "https://research.elamur.ai/free/en/shelves/nlp/page/15/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/shelves/nlp/page/15/) [home](https://md.research.elamur.ai/free/en/) / [shelves](https://md.research.elamur.ai/free/en/shelves/) / [Natural language processing](https://md.research.elamur.ai/free/en/shelves/nlp/) / page 15 # 💬 Natural language processing 2421 papers · page 15 of 97 · the most cited first · [all shelves](https://md.research.elamur.ai/free/en/shelves/) Computational linguistics from the ACL Anthology and arXiv: language models, information extraction, dialogue, evaluation. [← prev](https://md.research.elamur.ai/free/en/shelves/nlp/page/14/) [1](https://md.research.elamur.ai/free/en/shelves/nlp/) … [14](https://md.research.elamur.ai/free/en/shelves/nlp/page/14/) **15** [16](https://md.research.elamur.ai/free/en/shelves/nlp/page/16/) … [97](https://md.research.elamur.ai/free/en/shelves/nlp/page/97/) [next →](https://md.research.elamur.ai/free/en/shelves/nlp/page/16/) - [A Survey on Automated Fact-Checking](https://md.research.elamur.ai/free/en/papers/guo-2022-survey-automated-fact-checking/) — Zhijiang Guo, Michael Schlichtkrull, Andreas Vlachos · 2022 · 646 citations - [Incremental Joint Extraction of Entity Mentions and Relations](https://md.research.elamur.ai/free/en/papers/li-2014-incremental-joint-extraction-entity-mentions/) — Qi Li, Heng Ji · 2014 · 646 citations - [FLAIR: An Easy-to-Use Framework for State-of-the-Art NLP](https://md.research.elamur.ai/free/en/papers/akbik-2019-flair-easy-use-framework-state/) — Alan Akbik, Tanja Bergmann, Duncan Blythe, et al. · 2019 · 645 citations - [Pointing the Unknown Words](https://md.research.elamur.ai/free/en/papers/gulcehre-2016-pointing-unknown-words/) — Caglar Gulcehre, Sungjin Ahn, Ramesh Nallapati, et al. · 2016 · 642 citations - [ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledge](https://md.research.elamur.ai/free/en/papers/li-2023-chatdoctor-medical-chat-model-fine/) — Yunxiang Li, Zihan Li, Kai Zhang, et al. · 2023 · 640 citations - [Learning Word Vectors for 157 Languages](https://md.research.elamur.ai/free/en/papers/grave-2018-learning-word-vectors-157-languages/) — Edouard Grave, Piotr Bojanowski, Prakhar Gupta, et al. · 2018 · 640 citations - [A Centering Approach to Pronouns](https://md.research.elamur.ai/free/en/papers/brennan-1987-centering-approach-pronouns/) — Susan E. Brennan, Marilyn W. Friedman, Carl J. Pollard · 1987 · 639 citations - [Scalable Inference and Training of Context-Rich Syntactic Translation Models](https://md.research.elamur.ai/free/en/papers/galley-2006-scalable-inference-training-context-rich/) — Michel Galley, Jonathan Graehl, Kevin Knight, et al. · 2006 · 638 citations - [Arabic Tokenization, Part-of-Speech Tagging and Morphological Disambiguation in One Fell Swoop](https://md.research.elamur.ai/free/en/papers/aclbulk-2005-habash-arabic-tokenization-part-speech-tagging/) — Nizar Habash, Owen Rambow · 2005 · 634 citations - [Discriminating Gender on Twitter](https://md.research.elamur.ai/free/en/papers/burger-2011-discriminating-gender-twitter/) — John D. Burger, John Henderson, George Kim, et al. · 2011 · 631 citations - [Exploring Content Models for Multi-Document Summarization](https://md.research.elamur.ai/free/en/papers/haghighi-2009-exploring-content-models-multi-document/) — Aria Haghighi, Lucy Vanderwende · 2009 · 630 citations - [Sequential Matching Network: A New Architecture for Multi-turn Response Selection in Retrieval-Based Chatbots](https://md.research.elamur.ai/free/en/papers/wu-2017-sequential-matching-network-new-architecture/) — Yu Wu, Wei Wu, Chen Xing, et al. · 2017 · 624 citations - [LayoutLMv2: Multi-modal Pre-training for Visually-rich Document Understanding](https://md.research.elamur.ai/free/en/papers/xu-2021-layoutlmv2-multi-modal-pre-training/) — Yang Xu, Yiheng Xu, Tengchao Lv, et al. · 2021 · 623 citations - [Efficient Intent Detection with Dual Sentence Encoders](https://md.research.elamur.ai/free/en/papers/casanueva-2020-efficient-intent-detection-dual-sentence/) — Iñigo Casanueva, Tadas Temčinas, Daniela Gerz, et al. · 2020 · 622 citations - [Learning to Paraphrase: An Unsupervised Approach Using Multiple-Sequence Alignment](https://md.research.elamur.ai/free/en/papers/barzilay-2003-learning-paraphrase-unsupervised-approach-multiple/) — Regina Barzilay, Lillian Lee · 2003 · 622 citations - [Harnessing Deep Neural Networks with Logic Rules](https://md.research.elamur.ai/free/en/papers/hu-2016-harnessing-deep-neural-networks-logic/) — Zhiting Hu, Xuezhe Ma, Zhengzhong Liu, et al. · 2016 · 619 citations - [Object Hallucination in Image Captioning](https://md.research.elamur.ai/free/en/papers/rohrbach-2018-object-hallucination-image-captioning/) — Anna Rohrbach, Lisa Anne Hendricks, Kaylee Burns, et al. · 2018 · 617 citations - [Parsing Argumentation Structures in Persuasive Essays](https://md.research.elamur.ai/free/en/papers/stab-2017-parsing-argumentation-structures-persuasive-essays/) — Christian Stab, Iryna Gurevych · 2017 · 613 citations - [Classifying Relations by Ranking with Convolutional Neural Networks](https://md.research.elamur.ai/free/en/papers/santos-2015-classifying-relations-ranking-convolutional-neural/) — Cícero dos Santos, Bing Xiang, Bowen Zhou · 2015 · 613 citations - [Opinosis: A Graph Based Approach to Abstractive Summarization of Highly Redundant Opinions](https://md.research.elamur.ai/free/en/papers/ganesan-2010-opinosis-graph-based-approach-abstractive/) — Kavita Ganesan, ChengXiang Zhai, Jiawei Han · 2010 · 608 citations - [Extracting Relational Facts by an End-to-End Neural Model with Copy Mechanism](https://md.research.elamur.ai/free/en/papers/zeng-2018-extracting-relational-facts-end-end/) — Xiangrong Zeng, Daojian Zeng, Shizhu He, et al. · 2018 · 607 citations - [Event Extraction by Answering (Almost) Natural Questions](https://md.research.elamur.ai/free/en/papers/du-2020-event-extraction-answering-almost-natural/) — Xinya Du, Claire Cardie · 2020 · 602 citations - [RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/qu-2021-rocketqa-optimized-training-approach-dense/) — Yingqi Qu, Yuchen Ding, Jing Liu, et al. · 2021 · 601 citations - [Argument Mining: A Survey](https://md.research.elamur.ai/free/en/papers/lawrence-2019-argument-mining-survey/) — John Lawrence, Chris Reed · 2019 · 601 citations - [A Joint Neural Model for Information Extraction with Global Features](https://md.research.elamur.ai/free/en/papers/lin-2020-joint-neural-model-information-extraction/) — Ying Lin, Heng Ji, Fei Huang, et al. · 2020 · 600 citations [← prev](https://md.research.elamur.ai/free/en/shelves/nlp/page/14/) [1](https://md.research.elamur.ai/free/en/shelves/nlp/) … [14](https://md.research.elamur.ai/free/en/shelves/nlp/page/14/) **15** [16](https://md.research.elamur.ai/free/en/shelves/nlp/page/16/) … [97](https://md.research.elamur.ai/free/en/shelves/nlp/page/97/) [next →](https://md.research.elamur.ai/free/en/shelves/nlp/page/16/)