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Unlock the potential of Kolmogorov-Arnold Networks with WS-KAN, a weight-space architecture that understands their hidden symmetries and predicts their performance far better than generic methods.
Forget monolithic LoRAs: LoRWeB dynamically mixes a basis set of LoRAs to unlock SOTA generalization in visual analogy tasks.
