Control Prefixes for Parameter-Efficient Text Generation. (arXiv:2110.08329v2 [cs.CL] UPDATED)

Web: http://arxiv.org/abs/2110.08329

Prefix-tuning is a powerful lightweight technique for adapting a large
pre-trained language model to a downstream application. However, it uses the
same dataset-level tuned prompt for all examples in the dataset. We extend this
idea and propose a dynamic method, Control Prefixes, which allows for the
inclusion of conditional input-dependent information, combining the benefits of
prompt tuning and controlled generation. The method incorporates
attribute-level learnable representations into different layers of a
pre-trained transformer, allowing for the generated text to be …

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