@inproceedings{ju-etal-2023-continuous,
title = "Is Continuous Prompt a Combination of Discrete Prompts? Towards a Novel View for Interpreting Continuous Prompts",
author = "Ju, Tianjie and
Zheng, Yubin and
Wang, Hanyi and
Zhao, Haodong and
Liu, Gongshen",
editor = "Rogers, Anna and
Boyd-Graber, Jordan and
Okazaki, Naoaki",
booktitle = "Findings of the Association for Computational Linguistics: ACL 2023",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.findings-acl.494",
doi = "10.18653/v1/2023.findings-acl.494",
pages = "7804--7819",
abstract = "The broad adoption of continuous prompts has brought state-of-the-art results on a diverse array of downstream natural language processing (NLP) tasks. Nonetheless, little attention has been paid to the interpretability and transferability of continuous prompts. Faced with the challenges, we investigate the feasibility of interpreting continuous prompts as the weighting of discrete prompts by jointly optimizing prompt fidelity and downstream fidelity. Our experiments show that: (1) one can always find a combination of discrete prompts as the replacement of continuous prompts that performs well on downstream tasks; (2) our interpretable framework faithfully reflects the reasoning process of source prompts; (3) our interpretations provide effective readability and plausibility, which is helpful to understand the decision-making of continuous prompts and discover potential shortcuts. Moreover, through the bridge constructed between continuous prompts and discrete prompts using our interpretations, it is promising to implement the cross-model transfer of continuous prompts without extra training signals. We hope this work will lead to a novel perspective on the interpretations of continuous prompts.",
}
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<abstract>The broad adoption of continuous prompts has brought state-of-the-art results on a diverse array of downstream natural language processing (NLP) tasks. Nonetheless, little attention has been paid to the interpretability and transferability of continuous prompts. Faced with the challenges, we investigate the feasibility of interpreting continuous prompts as the weighting of discrete prompts by jointly optimizing prompt fidelity and downstream fidelity. Our experiments show that: (1) one can always find a combination of discrete prompts as the replacement of continuous prompts that performs well on downstream tasks; (2) our interpretable framework faithfully reflects the reasoning process of source prompts; (3) our interpretations provide effective readability and plausibility, which is helpful to understand the decision-making of continuous prompts and discover potential shortcuts. Moreover, through the bridge constructed between continuous prompts and discrete prompts using our interpretations, it is promising to implement the cross-model transfer of continuous prompts without extra training signals. We hope this work will lead to a novel perspective on the interpretations of continuous prompts.</abstract>
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%0 Conference Proceedings
%T Is Continuous Prompt a Combination of Discrete Prompts? Towards a Novel View for Interpreting Continuous Prompts
%A Ju, Tianjie
%A Zheng, Yubin
%A Wang, Hanyi
%A Zhao, Haodong
%A Liu, Gongshen
%Y Rogers, Anna
%Y Boyd-Graber, Jordan
%Y Okazaki, Naoaki
%S Findings of the Association for Computational Linguistics: ACL 2023
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F ju-etal-2023-continuous
%X The broad adoption of continuous prompts has brought state-of-the-art results on a diverse array of downstream natural language processing (NLP) tasks. Nonetheless, little attention has been paid to the interpretability and transferability of continuous prompts. Faced with the challenges, we investigate the feasibility of interpreting continuous prompts as the weighting of discrete prompts by jointly optimizing prompt fidelity and downstream fidelity. Our experiments show that: (1) one can always find a combination of discrete prompts as the replacement of continuous prompts that performs well on downstream tasks; (2) our interpretable framework faithfully reflects the reasoning process of source prompts; (3) our interpretations provide effective readability and plausibility, which is helpful to understand the decision-making of continuous prompts and discover potential shortcuts. Moreover, through the bridge constructed between continuous prompts and discrete prompts using our interpretations, it is promising to implement the cross-model transfer of continuous prompts without extra training signals. We hope this work will lead to a novel perspective on the interpretations of continuous prompts.
%R 10.18653/v1/2023.findings-acl.494
%U https://aclanthology.org/2023.findings-acl.494
%U https://doi.org/10.18653/v1/2023.findings-acl.494
%P 7804-7819
Markdown (Informal)
[Is Continuous Prompt a Combination of Discrete Prompts? Towards a Novel View for Interpreting Continuous Prompts](https://aclanthology.org/2023.findings-acl.494) (Ju et al., Findings 2023)
ACL