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Large language models (LLMs) have demonstrated impressive abilities in generating unstructured natural language according to instructions.
Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, and Jamie Brew. 2019 · 1910
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Information extraction
Jim Cowie and Wendy Lehnert. 1996 · 1996
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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 linear programming formulation for global inference in natural language tasks
Dan Roth and Wen-tau Yih. 2004 · 2004
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NCBI disease corpus: A resource for disease name recognition and concept normalization
Rezarta Islamaj Dogan, Robert Leaman, and Zhiyong Lu. 2014 · 2014
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Biocreative V CDR task corpus: a resource for chemical disease relation extraction
Jiao Li, Yueping Sun, Robin J. Johnson, Daniela Sciaky, Chih-Hsuan Wei, Robert Leaman, Allan Peter Davis, Carolyn J. Mattingly, Thomas C. Wiegers, and Zhiyong Lu. 2016 · 2016
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Fewrel: A large-scale supervised few-shot relation classification dataset with state-of-the-art evaluation
Xu Han, Hao Zhu, Pengfei Yu, Ziyun Wang, Yuan Yao, Zhiyuan Liu, and Maosong Sun. 2018 · 2018
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Learning to reweight examples for robust deep learning
Mengye Ren, Wenyuan Zeng, Bin Yang, and Raquel Urtasun. 2018 · 2018
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Extracting relational facts by an end-to-end neural model with copy mechanism
Xiangrong Zeng, Daojian Zeng, Shizhu He, Kang Liu, and Jun Zhao. 2018 · 2018
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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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Opennre: An open and extensible toolkit for neural relation extraction
Xu Han, Tianyu Gao, Yuan Yao, Deming Ye, Zhiyuan Liu, and Maosong Sun. 2019 · 2019
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2019 · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Köpf, Edward Z. Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019 · 2019
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Matching the blanks: Distributional similarity for relation learning
Livio Baldini Soares, Nicholas FitzGerald, Jeffrey Ling, and Tom Kwiatkowski. 2019 · 2019
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Learning to contextually aggregate multi-source supervision for sequence labeling
Ouyu Lan, Xiao Huang, Bill Yuchen Lin, He Jiang, Liyuan Liu, and Xiang Ren. 2020 · 2020
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BOND: bert-assisted open-domain named entity recognition with distant supervision
Chen Liang, Yue Yu, Haoming Jiang, Siawpeng Er, Ruijia Wang, Tuo Zhao, and Chao Zhang. 2020 · 2020
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Named entity recognition without labelled data: A weak supervision approach
Pierre Lison, Jeremy Barnes, Aliaksandr Hubin, and Samia Touileb. 2020 · 2020
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Denoising multi-source weak supervision for neural text classification
Wendi Ren, Yinghao Li, Hanting Su, David Kartchner, Cassie Mitchell, and Chao Zhang. 2020 · 2020
Cited alongside, same era.
Weakly supervised sequence tagging from noisy rules
Esteban Safranchik, Shiying Luo, and Stephen H. Bach. 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.
Bertifying the hidden markov model for multi-source weakly supervised named entity recognition
Yinghao Li, Pranav Shetty, Lucas Liu, Chao Zhang, and Le Song. 2021 · 2021
Cited alongside, same era.
skweak: Weak supervision made easy for NLP
Pierre Lison, Jeremy Barnes, and Aliaksandr Hubin. 2021 · 2021
Cited alongside, same era.
Fine-tuning pre-trained language model with weak supervision: A contrastive-regularized self-training approach
Debertav3: Improving deberta using electra-style pre-training with gradient-disentangled embedding sharing
Pengcheng He, Jianfeng Gao, and Weizhu Chen. 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, Lélio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed. 2023 · 2023
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Instruct and extract: Instruction tuning for on-demand information extraction
Yizhu Jiao, Ming Zhong, Sha Li, Ruining Zhao, Siru Ouyang, Heng Ji, and Jiawei Han. 2023 · 2023
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Efficient memory management for large language model serving with pagedattention
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph E. Gonzalez, Hao Zhang, and Ion Stoica. 2023 · 2023
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Extracting shopping interest-related product types from the web
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Yue Yu, Simiao Zuo, Haoming Jiang, Wendi Ren, Tuo Zhao, and Chao Zhang. 2021 · 2021
Cited alongside, same era.
WRENCH: A comprehensive benchmark for weak supervision
Jieyu Zhang, Yue Yu, Yinghao Li, Yujing Wang, Yaming Yang, Mao Yang, and Alexander Ratner. 2021 · 2021
Cited alongside, same era.
Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
Cited alongside, same era.
Training subset selection for weak supervision
Hunter Lang, Aravindan Vijayaraghavan, and David A. Sontag. 2022 · 2022
Cited alongside, same era.
Sparse conditional hidden markov model for weakly supervised named entity recognition
Yinghao Li, Le Song, and Chao Zhang. 2022 · 2022
Cited alongside, same era.
Decomposed meta-learning for few-shot named entity recognition
Tingting Ma, Huiqiang Jiang, Qianhui Wu, Tiejun Zhao, and Chin-Yew Lin. 2022 · 2022
Cited alongside, same era.
Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul F. Christiano, Jan Leike, and Ryan Lowe. 2022 · 2022
Cited alongside, same era.
Yinghao Li, Colin Lockard, Prashant Shiralkar, and Chao Zhang. 2023a · 2023
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Type-aware decomposed framework for few-shot named entity recognition
Yongqi Li, Yu Yu, and Tieyun Qian. 2023b · 2023
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Introducing ChatGPT
OpenAI. 2022 · 2023
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OpenAI. 2023 · 2023
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Gollie: Annotation guidelines improve zero-shot information-extraction
Oscar Sainz, Iker García-Ferrero, Rodrigo Agerri, Oier Lopez de Lacalle, German Rigau, and Eneko Agirre. 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, Dan Bikel, Lukas Blecher, Cristian Canton-Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, Wenyin Fu, Brian Fuller, Cynthia Gao, Vedanuj Goswami, Naman Goyal, Anthony Hartshorn, Saghar Hosseini, Rui Hou, Hakan Inan, Marcin Kardas, Viktor Kerkez, Madian Khabsa, Isabel Kloumann, Artem Korenev, Punit Singh Koura, Marie-Anne Lachaux, Thibaut Lavril, Jenya Lee, Diana Liskovich, Yinghai Lu, Yuning Mao, Xavier Martinet, Todor Mihaylov, Pushkar Mishra, Igor Molybog, Yixin Nie, Andrew Poulton, Jeremy Reizenstein, Rashi Rungta, Kalyan Saladi, Alan Schelten, Ruan Silva, Eric Michael Smith, Ranjan Subramanian, Xiaoqing Ellen Tan, Binh Tang, Ross Taylor, Adina Williams, Jian Xiang Kuan, Puxin Xu, Zheng Yan, Iliyan Zarov, Yuchen Zhang, Angela Fan, Melanie Kambadur, Sharan Narang, Aurélien Rodriguez, Robert Stojnic, Sergey Edunov, and Thomas Scialom. 2023 · 2023
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Self-consistency improves chain of thought reasoning in language models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou. 2023c · 2023
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Empirical study of zero-shot NER with chatgpt
Tingyu Xie, Qi Li, Jian Zhang, Yan Zhang, Zuozhu Liu, and Hongwei Wang. 2023 · 2023
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Gliner: Generalist model for named entity recognition using bidirectional transformer
Urchade Zaratiana, Nadi Tomeh, Pierre Holat, and Thierry Charnois. 2023 · 2023
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Aligning instruction tasks unlocks large language models as zero-shot relation extractors
Kai Zhang, Bernal Jimenez Gutierrez, and Yu Su. 2023 · 2023
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Universalner: Targeted distillation from large language models for open named entity recognition
Wenxuan Zhou, Sheng Zhang, Yu Gu, Muhao Chen, and Hoifung Poon. 2023 · 2023
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Weaker than you think: A critical look at weakly supervised learning
Dawei Zhu, Xiaoyu Shen, Marius Mosbach, Andreas Stephan, and Dietrich Klakow. 2023 · 2023
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Albert Q. Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de Las Casas, Emma Bou Hanna, Florian Bressand, Gianna Lengyel, Guillaume Bour, Guillaume Lample, Lélio Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Sandeep Subramanian, Sophia Yang, Szymon Antoniak, Teven Le Scao, Théophile Gervet, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed. 2024 · 2024
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