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Despite the importance of relation extraction in building and representing knowledge, less research is focused on generalizing to unseen relations types.
Ctrl: A conditional transformer language model for controllable generation
Nitish Shirish Keskar, Bryan McCann, Lav R Varshney, Caiming Xiong, and Richard Socher. 2019 · 1909
Earlier work this paper cites.
Zero-shot text classification with generative language models
Raul Puri and Bryan Catanzaro. 2019 · 1912
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A neural probabilistic language model
Yoshua Bengio, Réjean Ducharme, Pascal Vincent, and Christian Janvin. 2001 · 2001
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DARE: data augmented relation extraction with GPT-2
Yannis Papanikolaou and Andrea Pierleoni. 2020 · 2004
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Distilling the knowledge in a neural network
Geoffrey E. Hinton, Oriol Vinyals, and Jeffrey Dean. 2015 · 2015
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Learning entity and relation embeddings for knowledge graph completion
Yankai Lin, Zhiyuan Liu, Maosong Sun, Yang Liu, and Xuan Zhu. 2015 · 2015
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Reasoning about entailment with neural attention
Tim Rocktäschel, Edward Grefenstette, Karl Moritz Hermann, Tomás Kociský, and Phil Blunsom. 2016 · 2016
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Question answering on freebase via relation extraction and textual evidence
Kun Xu, Siva Reddy, Yansong Feng, Songfang Huang, and Dongyan Zhao. 2016 · 2016
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Distant supervision for relation extraction with sentence-level attention and entity descriptions
Guoliang Ji, Kang Liu, Shizhu He, and Jun Zhao. 2017 · 2017
Earlier work this paper cites.
Zero-shot relation extraction via reading comprehension
Omer Levy, Minjoon Seo, Eunsol Choi, and Luke Zettlemoyer. 2017 · 2017
Earlier work this paper cites.
Train once, test anywhere: Zero-shot learning for text classification
Pushpankar Kumar Pushp and Muktabh Mayank Srivastava. 2017 · 2017
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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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Zero-shot transfer learning for event extraction
Lifu Huang, Heng Ji, Kyunghyun Cho, Ido Dagan, Sebastian Riedel, and Clare Voss. 2018 · 2018
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Contextual augmentation: Data augmentation by words with paradigmatic relations
Sosuke Kobayashi. 2018 · 2018
Earlier work this paper cites.
Zero-shot relation classification as textual entailment
Abiola Obamuyide and Andreas Vlachos. 2018 · 2018
Cited alongside, same era.
Relation extraction using distant supervision: A survey
Alisa Smirnova and Philippe Cudré-Mauroux. 2018 · 2018
Cited alongside, same era.
Entity-relation extraction as multi-turn question answering
Xiaoya Li, Fan Yin, Zijun Sun, Xiayu Li, Arianna Yuan, Duo Chai, Mingxin Zhou, and Jiwei Li. 2019 · 2019
Cited alongside, same era.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2019 · 2019
Cited alongside, same era.
Language models as knowledge bases?
Fabio Petroni, Tim Rocktäschel, Sebastian Riedel, Patrick Lewis, Anton Bakhtin, Yuxiang Wu, and Alexander Miller. 2019 · 2019
Cited alongside, same era.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
Two are better than one: Joint entity and relation extraction with table-sequence encoders
Jue Wang and Wei Lu. 2020 · 2020
Later among the works it cites.
Unsupervised data augmentation for consistency training
Qizhe Xie, Zihang Dai, Eduard Hovy, Thang Luong, and Quoc Le. 2020 · 2020
Later among the works it cites.
Leveraging type descriptions for zero-shot named entity recognition and classification
Rami Aly, Andreas Vlachos, and Ryan McDonald. 2021 · 2021
Later among the works it cites.
Zs-bert: Towards zero-shot relation extraction with attribute representation learning
Chih-Yao Chen and Cheng-Te Li. 2021 · 2021
Later among the works it cites.
Template-based named entity recognition using BART
Leyang Cui, Yu Wu, Jian Liu, Sen Yang, and Yue Zhang. 2021 · 2021
Later among the works it cites.
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Cited alongside, same era.
A survey of zero-shot learning: Settings, methods, and applications
Wei Wang, Vincent W. Zheng, Han Yu, and Chunyan Miao. 2019 · 2019
Cited alongside, same era.
Eda: Easy data augmentation techniques for boosting performance on text classification tasks
Jason Wei and Kai Zou. 2019 · 2019
Cited alongside, same era.
Enriching pre-trained language model with entity information for relation classification
Shanchan Wu and Yifan He. 2019 · 2019
Cited alongside, same era.
DAGA: Data augmentation with a generation approach for low-resource tagging tasks
Bosheng Ding, Linlin Liu, Lidong Bing, Canasai Kruengkrai, Thien Hai Nguyen, Shafiq Joty, Luo Si, and Chunyan Miao. 2020 · 2020
Cited alongside, same era.
Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
Cited alongside, same era.
Effective modeling of encoder-decoder architecture for joint entity and relation extraction
Tapas Nayak and Hwee Tou Ng. 2020 · 2020
Cited alongside, same era.
Kenton Lee, Kelvin Guu, Luheng He, Tim Dozat, and Hyung Won Chung. 2021 · 2021
Later among the works it cites.
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig. 2021 · 2021
Later among the works it cites.
Prompt programming for large language models: Beyond the few-shot paradigm
Laria Reynolds and Kyle McDonell. 2021 · 2021
Later among the works it cites.
Learning span-level interactions for aspect sentiment triplet extraction
Lu Xu, Yew Ken Chia, and Lidong Bing. 2021 · 2021
Later among the works it cites.
Calibrate before use: Improving few-shot performance of language models
Zihao Zhao, Eric Wallace, Shi Feng, Dan Klein, and Sameer Singh. 2021 · 2021
Later among the works it cites.
Meta-tuning language models to answer prompts better
Ruiqi Zhong, Kristy Lee, Zheng Zhang, and Dan Klein. 2021 · 2021
Later among the works it cites.
A frustratingly easy approach for entity and relation extraction
Zexuan Zhong and Danqi Chen. 2021 · 2021
Later among the works it cites.
Generating training data with language models: Towards zero-shot language understanding
Yu Meng, Jiaxin Huang, Yu Zhang, and Jiawei Han. 2022 · 2022
Closest in time.
Zerogen: Efficient zero-shot learning via dataset generation
Jiacheng Ye, Jiahui Gao, Qintong Li, Hang Xu, Jiangtao Feng, Zhiyong Wu, Tao Yu, and Lingpeng Kong. 2022 · 2022
Closest in time.