Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning

Prompt tuning, in which prompts are optimized to adapt large-scale pre-trained language models to downstream tasks instead of fine-tuning the full model parameters, has been shown to be particularly effective when the prompts are trained in a multi-task transfer learning setting. These methods gener...

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Veröffentlicht in:	arXiv.org 2024-02
Hauptverfasser:	Lee, Haeju, Jeong, Minchan, Se-Young, Yun, Kim, Kee-Eung
Format:	Artikel
Sprache:	eng
Schlagworte:	Bayesian analysis Computer Science - Computation and Language Machine learning Mathematical models Parameters
Online-Zugang:	Volltext
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