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2024 ICML ICML 2024

One Size Fits All for Semantic Shifts: Adaptive Prompt Tuning for Continual Learning

Abstract

No abstract available. No abstract was captured for this paper when its proceedings were scraped - most often an older edition published without one online. How the corpus is built.

Authors

Doyoung Kim, Susik Yoon, Dongmin Park, Youngjun Lee, Hwanjun Song, Jihwan Bang, Jae-Gil Lee

Topics

Machine Learning > Application Areas > Domain Adaptation Deep Learning > Architectures > Transformers Artificial Intelligence > Core AI > Large Language Models

Keywords

continual learning transformer semantic shift prompt tuning adaptive prompting large language model
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