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- W3205067433 abstract "Prompting has recently been shown as a promising approach for applying pre-trained language models to perform downstream tasks. We present Multi-Stage Prompting, a simple and automatic approach for leveraging pre-trained language models to translation tasks. To better mitigate the discrepancy between pre-training and translation, MSP divides the translation process via pre-trained language models into three separate stages: the encoding stage, the re-encoding stage, and the decoding stage. During each stage, we independently apply different continuous prompts for allowing pre-trained language models better shift to translation tasks. We conduct extensive experiments on three translation tasks. Experiments show that our method can significantly improve the translation performance of pre-trained language models." @default.
- W3205067433 created "2021-10-25" @default.
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- W3205067433 date "2022-01-01" @default.
- W3205067433 modified "2023-10-18" @default.
- W3205067433 title "MSP: Multi-Stage Prompting for Making Pre-trained Language Models Better Translators" @default.
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- W3205067433 doi "https://doi.org/10.18653/v1/2022.acl-long.424" @default.
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