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We introduce a method for improving the structural understanding abilities of language models.
The ATIS spoken language systems pilot corpus
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Multitask learning
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Gabor Angeli, Melvin Jose Johnson Premkumar, and Christopher D. Manning. 2015 · 2015
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Table filling multi-task recurrent neural network for joint entity and relation extraction
Pankaj Gupta, Hinrich Schütze, and Bernt Andrassy. 2016 · 2016
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Which coreference evaluation metric do you trust? a proposal for a link-based entity aware metric
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Demonyms and compound relational nouns in nominal open ie
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Gabriel Stanovsky and Ido Dagan. 2016 · 2016
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Language models are few-shot learners
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Jun Chen, Robert Hoehndorf, Mohamed Elhoseiny, and Xiangliang Zhang. 2020 · 2020
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Multiwoz 2.1: A consolidated multi-domain dialogue dataset with state corrections and state tracking baselines
Mihail Eric, Rahul Goel, Shachi Paul, Abhishek Sethi, Sanchit Agarwal, Shuyang Gao, Adarsh Kumar, Anuj Kumar Goyal, Peter Ku, and Dilek Hakkani-Tür. 2020 · 2020
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A simple language model for task-oriented dialogue
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BART: denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
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Fewrel: A large-scale supervised few-shot relation classification dataset with state-of-the-art evaluation
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Higher-order coreference resolution with coarse-to-fine inference
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Large-scale multi-domain belief tracking with knowledge sharing
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Open information extraction from conjunctive sentences
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Gabriel Stanovsky, Julian Michael, Luke Zettlemoyer, and Ido Dagan. 2018 · 2018
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Cloze-driven pretraining of self-attention networks
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How context affects language models’ factual predictions
Fabio Petroni, Patrick S. H. Lewis, Aleksandra Piktus, Tim Rocktäschel, Yuxiang Wu, Alexander H. Miller, and Sebastian Riedel. 2020 · 2020
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Blank language models
Tianxiao Shen, Victor Quach, Regina Barzilay, and Tommi S. Jaakkola. 2020 · 2020
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Language models are open knowledge graphs
Chenguang Wang, Xiao Liu, and Dawn Song. 2020 · 2020
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Corefqa: Coreference resolution as query-based span prediction
Wei Wu, Fei Wang, Arianna Yuan, Fei Wu, and Jiwei Li. 2020 · 2020
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A relation-specific attention network for joint entity and relation extraction
Yue Yuan, Xiaofei Zhou, Shirui Pan, Qiannan Zhu, Zeliang Song, and Li Guo. 2020 · 2020
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Multiwoz 2.2 : A dialogue dataset with additional annotation corrections and state tracking baselines
Xiaoxue Zang, Abhinav Rastogi, Srinivas Sunkara, Raghav Gupta, Jianguo Zhang, and Jindong Chen. 2020 · 2020
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PEGASUS: pre-training with extracted gap-sentences for abstractive summarization
Jingqing Zhang, Yao Zhao, Mohammad Saleh, and Peter J. Liu. 2020 · 2020
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Asking effective and diverse questions: A machine reading comprehension based framework for joint entity-relation extraction
Tianyang Zhao, Zhao Yan, Yunbo Cao, and Zhoujun Li. 2020 · 2020
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Knowledge graph based synthetic corpus generation for knowledge-enhanced language model pre-training
Oshin Agarwal, Heming Ge, Siamak Shakeri, and Rami Al-Rfou. 2021 · 2021
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All NLP tasks are generation tasks: A general pretraining framework
Zhengxiao Du, Yujie Qian, Xiao Liu, Ming Ding, Jiezhong Qiu, Zhilin Yang, and Jie Tang. 2021 · 2021
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The pile: An 800gb dataset of diverse text for language modeling
Leo Gao, Stella Biderman, Sid Black, Laurence Golding, Travis Hoppe, Charles Foster, Jason Phang, Horace He, Anish Thite, Noa Nabeshima, Shawn Presser, and Connor Leahy. 2021 · 2021
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Cutting down on prompts and parameters: Simple few-shot learning with language models
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The power of scale for parameter-efficient prompt tuning
Brian Lester, Rami Al-Rfou, and Noah Constant. 2021 · 2021
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P-tuning v2: Prompt tuning can be comparable to fine-tuning universally across scales and tasks
Xiao Liu, Kaixuan Ji, Yicheng Fu, Zhengxiao Du, Zhilin Yang, and Jie Tang. 2021 · 2021
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Structured prediction as translation between augmented natural languages
Giovanni Paolini, Ben Athiwaratkun, Jason Krone, Jie Ma, Alessandro Achille, Rishita Anubhai, Cícero Nogueira dos Santos, Bing Xiang, and Stefano Soatto. 2021 · 2021
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Label verbalization and entailment for effective zero and few-shot relation extraction
Oscar Sainz, Oier Lopez de Lacalle, Gorka Labaka, Ander Barrena, and Eneko Agirre. 2021 · 2021
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Multitask prompted training enables zero-shot task generalization
Victor Sanh, Albert Webson, Colin Raffel, Stephen H. Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Teven Le Scao, Arun Raja, Manan Dey, M. Saiful Bari, Canwen Xu, Urmish Thakker, Shanya Sharma, Eliza Szczechla, Taewoon Kim, Gunjan Chhablani, Nihal V. Nayak, Debajyoti Datta, Jonathan Chang, Mike Tian-Jian Jiang, Han Wang, Matteo Manica, Sheng Shen, Zheng Xin Yong, Harshit Pandey, Rachel Bawden, Thomas Wang, Trishala Neeraj, Jos Rozen, Abheesht Sharma, Andrea Santilli, Thibault Févry, Jason Alan Fries, Ryan Teehan, Stella Biderman, Leo Gao, Tali Bers, Thomas Wolf, and Alexander M. Rush. 2021 · 2021
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It’s not just size that matters: Small language models are also few-shot learners
Timo Schick and Hinrich Schütze. 2021 · 2021
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Zero-shot information extraction as a unified text-to-triple translation
Chenguang Wang, Xiao Liu, Zui Chen, Haoyun Hong, Jie Tang, and Dawn Song. 2021 · 2021
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Finetuned language models are zero-shot learners
Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, and Quoc V. Le. 2021 · 2021
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Hang Yan, Tao Gui, Junqi Dai, Qipeng Guo, Zheng Zhang, and Xipeng Qiu. 2021 · 2021
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Wanrong Zhu, Zhiting Hu, and Eric P. Xing. 2019 · 2021
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