Papers with Soft-prompt tuning

1 papers
MPrompt: Exploring Multi-level Prompt Tuning for Machine Reading Comprehension (2023.findings-emnlp)

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Challenge: Existing soft prompt methods focus on designing the input-independent prompts that steer the model to fit the domain of the new dataset.
Approach: They propose a multi-level prompt tuning method that utilizes prompts at task-specific, domain-specific and context-specific levels to enhance the comprehension of input semantics.
Outcome: The proposed method improves on 12 benchmarks on various QA formats and achieves an average improvement of 1.94% over the state-of-the-art methods.

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