Researchers from the University of Washington and Allen Institute for AI Present Proxy-Tuning: An Efficient Alternative to Finetuning Large Language Models

The inherent capabilities of pretrained large language models are notable, yet achieving desired behaviors often requires additional adaptation. When dealing with models whose weights are kept private, the challenge intensifies, rendering tuning either excessively costly or outright impossible. As a result, striking the right balance between customization and resource efficiency remains a persistent concern in […]

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