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Prompt tuning, or the conditioning of a frozen pretrained language model (PLM) with soft prompts learned from data, has demonstrated impressive performance on a wide range of NLP tasks.
Language models are few-shot learners
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Openwebtext corpus
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Prefix-tuning: Optimizing continuous prompts for generation
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AdapterDrop: On the efficiency of adapters in transformers
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It’s not just size that matters: Small language models are also few-shot learners
Timo Schick and Hinrich Schütze. 2021b · 2021
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On transferability of prompt tuning for natural language understanding
Yusheng Su, Xiaozhi Wang, Yujia Qin, Chi-Min Chan, Yankai Lin, Zhiyuan Liu, Peng Li, Juanzi Li, Lei Hou, Maosong Sun, et al. 2021 · 2021
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