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Pretrained, large, generative language models (LMs) have had great success in a wide range of sequence tagging and structured prediction tasks.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2019 · 1910
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On faithfulness and factuality in abstractive summarization
Joshua Maynez, Shashi Narayan, Bernd Bohnet, and Ryan McDonald. 2020 · 1919
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Evaluation of spoken language systems: The atis domain
Patti Price. 1990 · 1990
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Alice Coucke, Alaa Saade, Adrien Ball, Théodore Bluche, Alexandre Caulier, David Leroy, Clément Doumouro, Thibault Gisselbrecht, Francesco Caltagirone, Thibaut Lavril, et al. 2018 · 2018
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A sequence-to-sequence model for semantic role labeling
Angel Daza and Anette Frank. 2018 · 2018
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(almost) zero-shot cross-lingual spoken language understanding
Shyam Upadhyay, Manaal Faruqui, Gokhan Tür, Hakkani-Tür Dilek, and Larry Heck. 2018 · 2018
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Cross-lingual transfer learning for multilingual task oriented dialog
Sebastian Schuster, Sonal Gupta, Rushin Shah, and Mike Lewis. 2019 · 2019
Cited alongside, same era.
Augmented natural language for generative sequence labeling
Ben Athiwaratkun, Cicero Nogueira dos Santos, Jason Krone, and Bing Xiang. 2020 · 2020
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Intent classification and slot filling for privacy policies
Wasi Ahmad, Jianfeng Chi, Tu Le, Thomas Norton, Yuan Tian, and Kai-Wei Chang. 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
Cited alongside, same era.
Multilingual code-switching for zero-shot cross-lingual intent prediction and slot filling
Jitin Krishnan, Antonios Anastasopoulos, Hemant Purohit, and Huzefa Rangwala. 2021 · 2021
Cited alongside, same era.
Prompt programming for large language models: Beyond the few-shot paradigm
Laria Reynolds and Kyle McDonell. 2021 · 2021
Later among the works it cites.
Towards zero-label language learning
Zirui Wang, Adams Wei Yu, Orhan Firat, and Yuan Cao. 2021 · 2021
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mT5: A massively multilingual pre-trained text-to-text transformer
Linting Xue, Noah Constant, Adam Roberts, Mihir Kale, Rami Al-Rfou, Aditya Siddhant, Aditya Barua, and Colin Raffel. 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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Adapting language models for zero-shot learning by meta-tuning on dataset and prompt collections
Ruiqi Zhong, Kristy Lee, Zheng Zhang, and Dan Klein. 2021 · 2021
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MTOP: A comprehensive multilingual task-oriented semantic parsing benchmark
Haoran Li, Abhinav Arora, Shuohui Chen, Anchit Gupta, Sonal Gupta, and Yashar Mehdad. 2021 · 2021
Cited alongside, same era.
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
Cited alongside, same era.
LFPT5: A unified framework for lifelong few-shot language learning based on prompt tuning of t5
Chengwei Qin and Shafiq Joty. 2022 · 2022
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