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Large language models (LLMs) have created a new paradigm for natural language processing.
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, et al. 2020 · 1901
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Simple bert models for relation extraction and semantic role labeling
Peng Shi and Jimmy Lin. 2019 · 1904
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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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DREEAM: Guiding attention with evidence for improving document-level relation extraction
Youmi Ma, An Wang, and Naoaki Okazaki. 2023 · 1983
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Distant supervision for relation extraction beyond the sentence boundary
Chris Quirk and Hoifung Poon. 2016 · 2016
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Chemical-induced disease relation extraction via convolutional neural network
Jinghang Gu, Fuqing Sun, Longhua Qian, and Guodong Zhou. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Position-aware attention and supervised data improve slot filling
Yuhao Zhang, Victor Zhong, Danqi Chen, Gabor Angeli, and Christopher D. Manning. 2017 · 2017
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Multi-task identification of entities, relations, and coreference for scientific knowledge graph construction
Yi Luan, Luheng He, Mari Ostendorf, and Hannaneh Hajishirzi. 2018 · 2018
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Angrosh Mandya, Danushka Bollegala, Frans Coenen, and Katie Atkinson. 2018 · 2018
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Simultaneously self-attending to all mentions for full-abstract biological relation extraction
Patrick Verga, Emma Strubell, and Andrew McCallum. 2018 · 2018
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Connecting the dots: Document-level neural relation extraction with edge-oriented graphs
Fenia Christopoulou, Makoto Miwa, and Sophia Ananiadou. 2019 · 2019
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Document-level n-ary relation extraction with multiscale representation learning
Robin Jia, Cliff Wong, and Hoifung Poon. 2019 · 2019
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2019 · 2019
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Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
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DocRED: A large-scale document-level relation extraction dataset
Yuan Yao, Deming Ye, Peng Li, Xu Han, Yankai Lin, Zhenghao Liu, Zhiyuan Liu, Lixin Huang, Jie Zhou, and Maosong Sun. 2019 · 2019
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A novel document-level relation extraction method based on bert and entity information
Xiaoyu Han and Lei Wang. 2020 · 2020
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Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, and Douwe Kiela. 2020 · 2020
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Graph enhanced dual attention network for document-level relation extraction
Bo Li, Wei Ye, Zhonghao Sheng, Rui Xie, Xiangyu Xi, and Shikun Zhang. 2020 · 2020
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Reasoning with latent structure refinement for document-level relation extraction
Guoshun Nan, Zhijiang Guo, Ivan Sekulic, and Wei Lu. 2020 · 2020
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Hin: Hierarchical inference network for document-level relation extraction
Hengzhu Tang, Yanan Cao, Zhenyu Zhang, Jiangxia Cao, Fang Fang, Shi Wang, and Pengfei Yin. 2020 · 2020
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Coreferential Reasoning Learning for Language Representation
Deming Ye, Yankai Lin, Jiaju Du, Zhenghao Liu, Peng Li, Maosong Sun, and Zhiyuan Liu. 2020 · 2020
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Learning to retrieve prompts for in-context learning
Ohad Rubin, Jonathan Herzig, and Jonathan Berant. 2022 · 2022
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Dual-channel and hierarchical graph convolutional networks for document-level relation extraction
Qi Sun, Tiancheng Xu, Kun Zhang, Kun Huang, Laishui Lv, Xun Li, Ting Zhang, and Doris Dore-Natteh. 2022 · 2022
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Document-level relation extraction with adaptive focal loss and knowledge distillation
Qingyu Tan, Ruidan He, Lidong Bing, and Hwee Tou Ng. 2022a · 2022
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Revisiting DocRED - addressing the false negative problem in relation extraction
Qingyu Tan, Lu Xu, Lidong Bing, Hwee Tou Ng, and Sharifah Mahani Aljunied. 2022b · 2022
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Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, brian ichter, Fei Xia, Ed Chi, Quoc V Le, and Denny Zhou. 2022 · 2022
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Double graph based reasoning for document-level relation extraction
Shuang Zeng, Runxin Xu, Baobao Chang, and Lei Li. 2020 · 2020
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Structured prediction as translation between augmented natural languages
Giovanni Paolini, Ben Athiwaratkun, Jason Krone, Jie Ma, Alessandro Achille, Rishita Anubhai, Cicero Nogueira dos Santos, Bing Xiang, and Stefano Soatto. 2021 · 2021
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True few-shot learning with language models
Ethan Perez, Douwe Kiela, and Kyunghyun Cho. 2021 · 2021
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Constrained language models yield few-shot semantic parsers
Richard Shin, Christopher Lin, Sam Thomson, Charles Chen, Subhro Roy, Emmanouil Antonios Platanios, Adam Pauls, Dan Klein, Jason Eisner, and Benjamin Van Durme. 2021 · 2021
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Calibrate before use: Improving few-shot performance of language models
Zihao Zhao, Eric Wallace, Shi Feng, Dan Klein, and Sameer Singh. 2021 · 2021
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Document-level relation extraction with adaptive thresholding and localized context pooling
Wenxuan Zhou, Kevin Huang, Tengyu Ma, and Jing Huang. 2021 · 2021
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Thinking about gpt-3 in-context learning for biomedical ie? think again
Bernal Jimenez Gutierrez, Nikolas McNeal, Clay Washington, You Chen, Lang Li, Huan Sun, and Yu Su. 2022 · 2022
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Document-level relation extraction with sentences importance estimation and focusing
Wang Xu, Kehai Chen, Lili Mou, and Tiejun Zhao. 2022 · 2022
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Relation-specific attentions over entity mentions for enhanced document-level relation extraction
Jiaxin Yu, Deqing Yang, and Shuyu Tian. 2022 · 2022
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A densely connected criss-cross attention network for document-level relation extraction
Liang Zhang and Yidong Cheng. 2022 · 2022
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Semi-automatic data enhancement for document-level relation extraction with distant supervision from large language models
Junpeng Li, Zixia Jia, and Zilong Zheng. 2023 · 2023
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In-context few-shot relation extraction via pre-trained language models
Yilmazcan Ozyurt, Stefan Feuerriegel, and Ce Zhang. 2023 · 2023
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When does in-context learning fall short and why? a study on specification-heavy tasks
Hao Peng, Xiaozhi Wang, Jianhui Chen, Weikai Li, Yunjia Qi, Zimu Wang, Zhili Wu, Kaisheng Zeng, Bin Xu, Lei Hou, et al. 2023 · 2023
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Revisiting relation extraction in the era of large language models
Somin Wadhwa, Silvio Amir, and Byron Wallace. 2023 · 2023
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GPT-RE: In-context learning for relation extraction using large language models
Zhen Wan, Fei Cheng, Zhuoyuan Mao, Qianying Liu, Haiyue Song, Jiwei Li, and Sadao Kurohashi. 2023 · 2023
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Autore: Document-level relation extraction with large language models
Xue Lilong, Zhang Dan, Dong Yuxiao, and Tang Jie. 2024 · 2024
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Qi Sun, Kun Huang, Xiaocui Yang, Rong Tong, Kun Zhang, and Soujanya Poria. 2024 · 2024
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Refining chatgpt for document-level relation extraction: A multi-dimensional prompting approach
Weiran Zhu, Xinzhi Wang, Xue Chen, and Xiangfeng Luo. 2024 · 2024
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