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Mar 6, 2023 · We present a unified dynamic prompt (DP) tuning strategy that dynamically determines different factors of prompts based on specific tasks and instances.
May 27, 2023 · Our endeavor encompasses a comprehensive theoretical analysis that unravels the potential benefits of optimizing the position for concatenating.
Abstract. It has been demonstrated that prompt tuning is highly effective in efficiently eliciting knowledge from language models (LMs).
Dynamic Prompting: A Unified Framework for Prompt Tuning: https://arxiv.org/abs/2303.02909. Special creadits to: OpenPrompt(https://github.com/thunlp/OpenPrompt).
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This study develops a keyword-optimized template insertion method (KOTI) and shows how optimizing position can improve performance on several clinical tasks.
Dynamic prompting in generative AI refers to a method where the input prompt given to an AI model is continuously adjusted based on the model's outputs or ...
Dynamic Prompting: A Unified Framework for Prompt Tuning: https://arxiv.org/abs/2303.02909. Special creadits to: OpenPrompt(https://github.com/thunlp/OpenPrompt).
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22 Citations · APrompt: Attention Prompt Tuning for Efficient Adaptation of Pre-trained Language Models · Dynamic Prompting: A Unified Framework for Prompt Tuning.