Papers by Xiaochen Liu

1 papers
PSP: Pre-trained Soft Prompts for Few-Shot Abstractive Summarization (2022.coling-1)

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Challenge: Experimental results show that our method outperforms full-model tuning in few-shot abstractive summarization tasks.
Approach: They propose a soft prompts architecture with prompt pre-training and prompt fine-tuning paradigm to support few-shot abstractive summarization.
Outcome: The proposed model outperforms Prompt Tuning and Profix-Tuning on CNN/DailyMail and XSum datasets and outperfies Profix Tuning by a large margin.

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