CRISP unifies model compression and parameter-efficient fine-tuning by decomposing weights into shared bases and small mixers, reporting 1-5% gains over prior dual-task and specialized methods.
BoolQ: Exploring the surprising difficulty of natural yes/no questions
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Decompose, Mix, Adapt: A Unified Framework for Parameter-Efficient Neural Network Recombination and Compression
CRISP unifies model compression and parameter-efficient fine-tuning by decomposing weights into shared bases and small mixers, reporting 1-5% gains over prior dual-task and specialized methods.