Black-box Prompt Learning for Pre-trained Language Models. (arXiv:2201.08531v1 [cs.CL])

Web: http://arxiv.org/abs/2201.08531

Domain-specific fine-tuning strategies for large pre-trained models received
vast attention in recent years. In previously studied settings, the model
architectures and parameters are tunable or at least visible, which we refer to
as white-box settings. This work considers a new scenario, where we do not have
access to a pre-trained model, except for its outputs given inputs, and we call
this problem black-box fine-tuning. To illustrate our approach, we first
introduce the black-box setting formally on text classification, where the …

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