Task-Feature Specialization explains weight disentanglement in task arithmetic and leads to orthogonality, which OrthoReg enforces to enhance performance of model composition methods.
arXiv preprint arXiv:2201.05337 , year=
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Activation Addition steers language models by adding contrastive activation vectors from prompt pairs to control high-level properties like sentiment and toxicity at inference time without training.
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Understanding and Enforcing Weight Disentanglement in Task Arithmetic
Task-Feature Specialization explains weight disentanglement in task arithmetic and leads to orthogonality, which OrthoReg enforces to enhance performance of model composition methods.
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Steering Language Models With Activation Engineering
Activation Addition steers language models by adding contrastive activation vectors from prompt pairs to control high-level properties like sentiment and toxicity at inference time without training.