A dataless regularizer based on Kronecker-Factored Approximate Curvature disentangles task vectors for improved task addition and negation in foundation models, with constant complexity and robustness to rescaling.
Semeval-2014 task 1: Evaluation of compositional distributional semantic models on full sentences through semantic relatedness and textual entailment
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Dataless Weight Disentanglement in Task Arithmetic via Kronecker-Factored Approximate Curvature
A dataless regularizer based on Kronecker-Factored Approximate Curvature disentangles task vectors for improved task addition and negation in foundation models, with constant complexity and robustness to rescaling.