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Large language models (LLMs) have become the preferred solution for many natural language processing tasks.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 1901
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Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
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Label Semantics for Few Shot Named Entity Recognition
Jie Ma, Miguel Ballesteros, Srikanth Doss, Rishita Anubhai, Sunil Mallya, Yaser Al-Onaizan, and Dan Roth. 2022a · 1971
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The unified medical language system
Donald AB Lindberg, Betsy L Humphreys, and Alexa T McCray. 1993 · 1993
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Aggregating UMLS Semantic Types for Reducing Conceptual Complexity
Alexa McCray, Anita Burgun, and Olivier Bodenreider. 2001 · 2001
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Introduction to the CoNLL-2002 shared task: Language-independent named entity recognition
Erik F. Tjong Kim Sang. 2002 · 2002
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Introduction to the CoNLL-2003 shared task: Language-independent named entity recognition
Erik F. Tjong Kim Sang and Fien De Meulder. 2003 · 2003
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A monolingual approach to contextualized word embeddings for mid-resource languages
Pedro Javier Ortiz Suárez, Laurent Romary, and Benoît Sagot. 2020 · 2006
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What can natural language processing do for clinical decision support?
Dina Demner-Fushman, Wendy W. Chapman, and Clement J. McDonald. 2009 · 2009
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2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text
Özlem Uzuner, Brett R South, Shuying Shen, and Scott L DuVall. 2011 · 2010
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Proposal for an Extension of Traditional Named Entities: From Guidelines to Evaluation, an Overview
Cyril Grouin, Sophie Rosset, Pierre Zweigenbaum, Karën Fort, Olivier Galibert, and Ludovic Quintard. 2011 · 2011
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Parallel data, tools and interfaces in OPUS
Jörg Tiedemann. 2012 · 2012
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Learning multilingual named entity recognition from Wikipedia
Joel Nothman, Nicky Ringland, Will Radford, Tara Murphy, and James R. Curran. 2013 · 2013
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NCBI disease corpus: A resource for disease name recognition and concept normalization
Rezarta Islamaj Doğan, Robert Leaman, and Zhiyong Lu. 2014 · 2014
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The QUAERO French medical corpus: A ressource for medical entity recognition and normalization
Aurélie Névéol, Cyril Grouin, Jeremy Leixa, Sophie Rosset, and Pierre Zweigenbaum. 2014 · 2014
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Challenges in clinical natural language processing for automated disorder normalization
Robert Leaman, Ritu Khare, and Zhiyong Lu. 2015 · 2015
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Aligning books and movies: Towards story-like visual explanations by watching movies and reading books
Yukun Zhu, Ryan Kiros, Rich Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, and Sanja Fidler. 2015 · 2015
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MIMIC-III, a freely accessible critical care database
Alistair EW Johnson, Tom J Pollard, Lu Shen, Li-wei H Lehman, Mengling Feng, Mohammad Ghassemi, Benjamin Moody, Peter Szolovits, Leo Anthony Celi, and Roger G Mark. 2016 · 2016
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A method for named entity normalization in biomedical articles: Application to diseases and plants
Hyejin Cho, Wonjun Choi, and Hyunju Lee. 2017 · 2017
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A novel data-driven workflow combining literature and electronic health records to estimate comorbidities burden for a specific disease: a case study on autoimmune comorbidities in patients with celiac disease
Jean-Baptiste Escudié, Bastien Rance, Georgia Malamut, Sherine Khater, Anita Burgun, Christophe Cellier, and Anne-Sophie Jannot. 2017 · 2017
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Reporting score distributions makes a difference: Performance study of LSTM-networks for sequence tagging
Nils Reimers and Iryna Gurevych. 2017 · 2017
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Data Statements for Natural Language Processing: Toward Mitigating System Bias and Enabling Better Science
Emily M. Bender and Batya Friedman. 2018 · 2018
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A French clinical corpus with comprehensive semantic annotations: development of the Medical Entity and Relation LIMSI annOtated Text corpus (MERLOT)
Leonardo Campillos, Louise Deléger, Cyril Grouin, Thierry Hamon, Anne-Laure Ligozat, and Aurélie Névéol. 2018 · 2018
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Clinical information extraction applications: A literature review
Yanshan Wang, Liwei Wang, Majid Rastegar-Mojarad, Sungrim Moon, Feichen Shen, Naveed Afzal, Sijia Liu, Yuqun Zeng, Saeed Mehrabi, Sunghwan Sohn, and Hongfang Liu. 2018 · 2018
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Publicly available clinical BERT embeddings
Emily Alsentzer, John Murphy, William Boag, Wei-Hung Weng, Di Jindi, Tristan Naumann, and Matthew McDermott. 2019 · 2019
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Deep Dominance - How to Properly Compare Deep Neural Models
Rotem Dror, Segev Shlomov, and Roi Reichart. 2019 · 2019
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Few-Shot Classification in Named Entity Recognition Task
Alexander Fritzler, Varvara Logacheva, and Maksim Kretov. 2019 · 2019
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Fine-tune BERT for Extractive Summarization
Yang Liu. 2019 · 2019
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The 2019 n2c2/UMass Lowell shared task on clinical concept normalization
Yen-Fu Luo, Sam Henry, Yanshan Wang, Feichen Shen, Ozlem Uzuner, and Anna Rumshisky. 2020 · 2019
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MCN: A comprehensive corpus for medical concept normalization
Yen-Fu Luo, Weiyi Sun, and Anna Rumshisky. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
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The Chilean waiting list corpus: a new resource for clinical named entity recognition in Spanish
Pablo Báez, Fabián Villena, Matías Rojas, Manuel Durán, and Jocelyn Dunstan. 2020 · 2020
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Spanish Pre-Trained BERT Model and Evaluation Data
José Cañete, Gabriel Chaperon, Rodrigo Fuentes, Jou-Hui Ho, Hojin Kang, and Jorge Pérez. 2020 · 2020
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Unsupervised Cross-lingual Representation Learning at Scale
Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer, and Veselin Stoyanov. 2020 · 2020
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The pile: An 800gb dataset of diverse text for language modeling
Leo Gao, Stella Biderman, Sid Black, Laurence Golding, Travis Hoppe, Charles Foster, Jason Phang, Horace He, Anish Thite, Noa Nabeshima, et al. 2020 · 2020
Cited alongside, same era.
Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network
Yutai Hou, Wanxiang Che, Yongkui Lai, Zhihan Zhou, Yijia Liu, Han Liu, and Ting Liu. 2020 · 2020
Cited alongside, same era.
SpanBERT: Improving Pre-training by Representing and Predicting Spans
Mandar Joshi, Danqi Chen, Yinhan Liu, Daniel S. Weld, Luke Zettlemoyer, and Omer Levy. 2020 · 2020
Cited alongside, same era.
FlauBERT: Unsupervised language model pre-training for French
Hang Le, Loïc Vial, Jibril Frej, Vincent Segonne, Maximin Coavoux, Benjamin Lecouteux, Alexandre Allauzen, Benoit Crabbé, Laurent Besacier, and Didier Schwab. 2020 · 2020
Cited alongside, same era.
A unified MRC framework for named entity recognition
BERN2: an advanced neural biomedical named entity recognition and normalization tool
Mujeen Sung, Minbyul Jeong, Yonghwa Choi, Donghyeon Kim, Jinhyuk Lee, and Jaewoo Kang. 2022 · 2022
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MedBERT: A Pre-trained Language Model for Biomedical Named Entity Recognition
Charangan Vasantharajan, Kyaw Zin Tun, Ho Thi-Nga, Sparsh Jain, Tong Rong, and Chng Eng Siong. 2022 · 2022
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Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al. 2022 · 2022
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Bloom: A 176b-parameter open-access multilingual language model
BigScience Workshop, Teven Le Scao, Angela Fan, Christopher Akiki, Ellie Pavlick, Suzana Ilić, Daniel Hesslow, Roman Castagné, Alexandra Sasha Luccioni, François Yvon, et al. 2022 · 2022
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alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Xiaoya Li, Jingrong Feng, Yuxian Meng, Qinghong Han, Fei Wu, and Jiwei Li. 2020 · 2020
Cited alongside, same era.
CamemBERT: a tasty French language model
Louis Martin, Benjamin Muller, Pedro Javier Ortiz Suárez, Yoann Dupont, Laurent Romary, Éric de la Clergerie, Djamé Seddah, and Benoît Sagot. 2020 · 2020
Cited alongside, same era.
How Context Affects Language Models’ Factual Predictions
Fabio Petroni, Patrick Lewis, Aleksandra Piktus, Tim Rocktäschel, Yuxiang Wu, Alexander H. Miller, and Sebastian Riedel. 2020 · 2020
Cited alongside, same era.
Simple and Effective Few-Shot Named Entity Recognition with Structured Nearest Neighbor Learning
Yi Yang and Arzoo Katiyar. 2020 · 2020
Cited alongside, same era.
Leveraging Type Descriptions for Zero-shot Named Entity Recognition and Classification
Rami Aly, Andreas Vlachos, and Ryan McDonald. 2021 · 2021
Cited alongside, same era.
Template-based named entity recognition using BART
Leyang Cui, Yu Wu, Jian Liu, Sen Yang, and Yue Zhang. 2021 · 2021
Cited alongside, same era.
Few-Shot Named Entity Recognition: An Empirical Baseline Study
Jiaxin Huang, Chunyuan Li, Krishan Subudhi, Damien Jose, Shobana Balakrishnan, Weizhu Chen, Baolin Peng, Jianfeng Gao, and Jiawei Han. 2021a · 2021
Cited alongside, same era.
Few-Shot Named Entity Recognition: An Empirical Baseline Study
Jiaxin Huang, Chunyuan Li, Krishan Subudhi, Damien Jose, Shobana Balakrishnan, Weizhu Chen, Baolin Peng, Jianfeng Gao, and Jiawei Han. 2021b · 2021
Cited alongside, same era.
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, et al. 2022 · 2022
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PromptNER: Prompting For Named Entity Recognition
Dhananjay Ashok and Zachary C. Lipton. 2023 · 2023
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Samy Ateia and Udo Kruschwitz. 2023 · 2023
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Few-shot learning for medical text: A review of advances, trends, and opportunities
Yao Ge, Yuting Guo, Sudeshna Das, Mohammed Ali Al-Garadi, and Abeed Sarker. 2023 · 2023
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Coverage-based Example Selection for In-Context Learning
Shivanshu Gupta, Matt Gardner, and Sameer Singh. 2023 · 2023
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MedAlpaca–An Open-Source Collection of Medical Conversational AI Models and Training Data
Tianyu Han, Lisa C Adams, Jens-Michalis Papaioannou, Paul Grundmann, Tom Oberhauser, Alexander Löser, Daniel Truhn, and Keno K Bressem. 2023 · 2023
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Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al. 2023 · 2023
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DrBERT: A robust pre-trained model in French for biomedical and clinical domains
Yanis Labrak, Adrien Bazoge, Richard Dufour, Mickael Rouvier, Emmanuel Morin, Béatrice Daille, and Pierre-Antoine Gourraud. 2023 · 2023
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ContrastNER: Contrastive-based Prompt Tuning for Few-shot NER
Amirhossein Layegh, Amir H Payberah, Ahmet Soylu, Dumitru Roman, and Mihhail Matskin. 2023 · 2023
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Parameter-Efficient Fine-Tuning without Introducing New Latency
Baohao Liao, Yan Meng, and Christof Monz. 2023 · 2023
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Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig. 2023 · 2023
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Large Language Models as Instructors: A Study on Multilingual Clinical Entity Extraction
Simon Meoni, Eric De la Clergerie, and Theo Ryffel. 2023 · 2023
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Guilherme Penedo, Quentin Malartic, Daniel Hesslow, Ruxandra Cojocaru, Alessandro Cappelli, Hamza Alobeidli, Baptiste Pannier, Ebtesam Almazrouei, and Julien Launay. 2023 · 2023
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PromptNER: Prompt locating and typing for named entity recognition
Yongliang Shen, Zeqi Tan, Shuhui Wu, Wenqi Zhang, Rongsheng Zhang, Yadong Xi, Weiming Lu, and Yueting Zhuang. 2023 · 2023
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Augustin Toma, Patrick R Lawler, Jimmy Ba, Rahul G Krishnan, Barry B Rubin, and Bo Wang. 2023 · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al. 2023 · 2023
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Prompting PaLM for translation: Assessing strategies and performance
David Vilar, Markus Freitag, Colin Cherry, Jiaming Luo, Viresh Ratnakar, and George Foster. 2023 · 2023
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Decomposed Two-Stage Prompt Learning for Few-Shot Named Entity Recognition
Feiyang Ye, Liang Huang, Senjie Liang, and KaiKai Chi. 2023 · 2023
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Judging LLM-as-a-judge with MT-Bench and Chatbot Arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric Xing, et al. 2023 · 2023
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Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
Marah Abdin, Sam Ade Jacobs, Ammar Ahmad Awan, et al. 2024 · 2024
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Leak, cheat, repeat: Data contamination and evaluation malpractices in closed-source LLMs
Simone Balloccu, Patrícia Schmidtová, Mateusz Lango, and Ondrej Dusek. 2024 · 2024
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Language inference-based learning for Low-Resource Chinese clinical named entity recognition using language model
Zhaojian Cui, Kai Yu, Zhenming Yuan, Xiaofeng Dong, and Weibin Luo. 2024 · 2024
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GPT for medical entity recognition in Spanish
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Improving large language models for clinical named entity recognition via prompt engineering
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A survey on recent advances in named entity recognition
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JobSkape: A framework for generating synthetic job postings to enhance skill matching
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CamemBERT-bio: Leveraging continual pre-training for cost-effective models on French biomedical data
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Enhancing phenotype recognition in clinical notes using large language models: PhenoBCBERT and PhenoGPT
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Prompt engineering paradigms for medical applications: Scoping review
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