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There has been increasing interest in exploring the capabilities of advanced large language models (LLMs) in the field of information extraction (IE), specifically focusing on tasks related to named entity recognition (NER) and relation extraction (RE).
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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The automatic content extraction (ACE) program - tasks, data, and evaluation
George R. Doddington, Alexis Mitchell, Mark A. Przybocki, Lance A. Ramshaw, Stephanie M. Strassel, and Ralph M. Weischedel. 2004 · 2004
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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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ACE 2005 Multilingual Training Corpus
C. Walker and Linguistic Data Consortium. 2005 · 2005
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Diego Mollá Aliod, Menno van Zaanen, and Daniel Smith. 2006 · 2006
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Neural architectures for named entity recognition
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Multi-task identification of entities, relations, and coreference for scientific knowledge graph construction
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Yunli Wang, Yu Wu, Lili Mou, Zhoujun Li, and Wenhan Chao. 2019 · 2019
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Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared 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 M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher 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 · 2020
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A unified MRC framework for named entity recognition
Xiaoya Li, Jingrong Feng, Yuxian Meng, Qinghong Han, Fei Wu, and Jiwei Li. 2020 · 2020
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Formality style transfer with shared latent space
Yunli Wang, Yu Wu, Lili Mou, Zhoujun Li, and Wenhan Chao. 2020 · 2020
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Named entity recognition as dependency parsing
Juntao Yu, Bernd Bohnet, and Massimo Poesio. 2020 · 2020
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Contrastive learning with hard negative samples
Joshua David Robinson, Ching-Yao Chuang, Suvrit Sra, and Stefanie Jegelka. 2021 · 2021
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A unified generative framework for various NER subtasks
Hang Yan, Tao Gui, Junqi Dai, Qipeng Guo, Zheng Zhang, and Xipeng Qiu. 2021 · 2021
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Multilingual machine translation systems from microsoft for WMT21 shared task
Jian Yang, Shuming Ma, Haoyang Huang, Dongdong Zhang, Li Dong, Shaohan Huang, Alexandre Muzio, Saksham Singhal, Hany Hassan, Xia Song, and Furu Wei. 2021a · 2021
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Learning to select relevant knowledge for neural machine translation
Jian Yang, Juncheng Wan, Shuming Ma, Haoyang Huang, Dongdong Zhang, Yong Yu, Zhoujun Li, and Furu Wei. 2021b · 2021
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Thinking about GPT-3 in-context learning for biomedical ie? think again
Bernal Jimenez Gutierrez, Nikolas McNeal, Clayton Washington, You Chen, Lang Li, Huan Sun, and Yu Su. 2022 · 2022
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What makes good in-context examples for gpt-3?
Jiachang Liu, Dinghan Shen, Yizhe Zhang, Bill Dolan, Lawrence Carin, and Weizhu Chen. 2022 · 2022
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Unified structure generation for universal information extraction
Yaojie Lu, Qing Liu, Dai Dai, Xinyan Xiao, Hongyu Lin, Xianpei Han, Le Sun, and Hua Wu. 2022 · 2022
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Rethinking the role of demonstrations: What makes in-context learning work?
Sewon Min, Xinxi Lyu, Ari Holtzman, Mikel Artetxe, Mike Lewis, Hannaneh Hajishirzi, and Luke Zettlemoyer. 2022 · 2022
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Complexity-based prompting for multi-step reasoning
Yao Fu, Hao Peng, Ashish Sabharwal, Peter Clark, and Tushar Khot. 2023 · 2023
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Codeie: Large code generation models are better few-shot information extractors
Peng Li, Tianxiang Sun, Qiong Tang, Hang Yan, Yuanbin Wu, Xuanjing Huang, and Xipeng Qiu. 2023b · 2023
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Z-ICL: zero-shot in-context learning with pseudo-demonstrations
Xinxi Lyu, Sewon Min, Iz Beltagy, Luke Zettlemoyer, and Hannaneh Hajishirzi. 2023 · 2023
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Chain of thought with explicit evidence reasoning for few-shot relation extraction
Xilai Ma, Jing Li, and Min Zhang. 2023 · 2023
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Multi-task transformer with relation-attention and type-attention for named entity recognition
Ying Mo, Hongyin Tang, Jiahao Liu, Qifan Wang, Zenglin Xu, Jingang Wang, Wei Wu, and Zhoujun Li. 2023a · 2023
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Chatgpt: Optimizing language models for dialogue
OpenAI. 2022 · 2022
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Learning to retrieve prompts for in-context learning
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CROP: zero-shot cross-lingual named entity recognition with multilingual labeled sequence translation
Jian Yang, Shaohan Huang, Shuming Ma, Yuwei Yin, Li Dong, Dongdong Zhang, Hongcheng Guo, Zhoujun Li, and Furu Wei. 2022a · 2022
Cited alongside, same era.
High-resource language-specific training for multilingual neural machine translation
Jian Yang, Yuwei Yin, Shuming Ma, Dongdong Zhang, Zhoujun Li, and Furu Wei. 2022b · 2022
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UM4: unified multilingual multiple teacher-student model for zero-resource neural machine translation
Jian Yang, Yuwei Yin, Shuming Ma, Dongdong Zhang, Shuangzhi Wu, Hongcheng Guo, Zhoujun Li, and Furu Wei. 2022c · 2022
Cited alongside, same era.
Packed levitated marker for entity and relation extraction
Deming Ye, Yankai Lin, Peng Li, and Maosong Sun. 2022 · 2022
Cited alongside, same era.
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Filtering, distillation, and hard negatives for vision-language pre-training
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Gollie: Annotation guidelines improve zero-shot information-extraction
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Llama 2: Open foundation and fine-tuned chat models
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Revisiting relation extraction in the era of large language models
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GPT-RE: in-context learning for relation extraction using large language models
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Code4struct: Code generation for few-shot event structure prediction
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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. 2023a · 2023
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Large language models for generative information extraction: A survey
Derong Xu, Wei Chen, Wenjun Peng, Chao Zhang, Tong Xu, Xiangyu Zhao, Xian Wu, Yefeng Zheng, and Enhong Chen. 2023 · 2023
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Ganlm: Encoder-decoder pre-training with an auxiliary discriminator
Jian Yang, Shuming Ma, Li Dong, Shaohan Huang, Haoyang Huang, Yuwei Yin, Dongdong Zhang, Liqun Yang, Furu Wei, and Zhoujun Li. 2023 · 2023
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A comprehensive survey on automatic knowledge graph construction
Lingfeng Zhong, Jia Wu, Qian Li, Hao Peng, and Xindong Wu. 2023 · 2023
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Multilingual machine translation with large language models: Empirical results and analysis
Wenhao Zhu, Hongyi Liu, Qingxiu Dong, Jingjing Xu, Lingpeng Kong, Jiajun Chen, Lei Li, and Shujian Huang. 2023 · 2023
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