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Relation extraction (RE) is a core task in natural language processing.
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, and 1 others. 2020 · 1901
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Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer. 2019 · 1910
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Semeval-2010 task 8: Multi-way classification of semantic relations between pairs of nominals
Iris Hendrickx, Su Nam Kim, Zornitsa Kozareva, Preslav Nakov, Diarmuid O Séaghdha, Sebastian Padó, Marco Pennacchiotti, Lorenza Romano, and Stan Szpakowicz. 2019 · 1911
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Policy invariance under reward transformations: Theory and application to reward shaping
Andrew Y Ng, Daishi Harada, and Stuart J Russell. 1999 · 1999
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Span-based joint entity and relation extraction with transformer pre-training
Markus Eberts and Adrian Ulges. 2020 · 2013
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Bidirectional recurrent convolutional neural network for relation classification
Rui Cai, Xiaodong Zhang, and Houfeng Wang. 2016 · 2016
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Semeval-2018 task 7: Semantic relation extraction and classification in scientific papers
Davide Buscaldi, Anne-Kathrin Schumann, Behrang Qasemizadeh, Haïfa Zargayouna, and Thierry Charnois. 2017 · 2018
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Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Alimekg: Domain knowledge graph construction and application in e-commerce
Feng-Lin Li, Hehong Chen, Guohai Xu, Tian Qiu, Feng Ji, Ji Zhang, and Haiqing Chen. 2020 · 2020
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Measuring mathematical problem solving with the math dataset
Dan Hendrycks, Collin Burns, Saurav Kadavath, Akul Arora, Steven Basart, Eric Tang, Dawn Song, and Jacob Steinhardt. 2021 · 2021
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Deep neural approaches to relation triplets extraction: a comprehensive survey
Tapas Nayak, Navonil Majumder, Pawan Goyal, and Soujanya Poria. 2021 · 2021
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A trigger-sense memory flow framework for joint entity and relation extraction
Yongliang Shen, Xinyin Ma, Yechun Tang, and Weiming Lu. 2021 · 2021
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Revisiting the negative data of distantly supervised relation extraction
Chenhao Xie, Jiaqing Liang, Jingping Liu, Chengsong Huang, Wenhao Huang, and Yanghua Xiao. 2021 · 2021
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Solving math word problems with process-and outcome-based feedback
Jonathan Uesato, Nate Kushman, Ramana Kumar, Francis Song, Noah Siegel, Lisa Wang, Antonia Creswell, Geoffrey Irving, and Irina Higgins. 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, and 1 others. 2022 · 2022
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Computational benefits of intermediate rewards for goal-reaching policy learning
Yuexiang Zhai, Christina Baek, Zhengyuan Zhou, Jiantao Jiao, and Yi Ma. 2022 · 2022
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Core: A few-shot company relation classification dataset for robust domain adaptation
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Suhas Kotha, Jacob Mitchell Springer, and Aditi Raghunathan. 2023 · 2023
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Revisiting relation extraction in the era of large language models
Somin Wadhwa, Silvio Amir, and Byron C Wallace. 2023 · 2023
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Gpt-re: In-context learning for relation extraction using large language models
A comprehensive survey on relation extraction: Recent advances and new frontiers
Xiaoyan Zhao, Yang Deng, Min Yang, Lingzhi Wang, Rui Zhang, Hong Cheng, Wai Lam, Ying Shen, and Ruifeng Xu. 2024 · 2024
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