IPL alternates discrete semantic token selection using approximate submodular optimization with continuous prompt optimization to boost both interpretability and task performance in vision-language model adaptation.
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Joint Semantic Token Selection and Prompt Optimization for Interpretable Prompt Learning
IPL alternates discrete semantic token selection using approximate submodular optimization with continuous prompt optimization to boost both interpretability and task performance in vision-language model adaptation.