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divyanshk committed Mar 11, 2024
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* Two main ones: adding adaptor layers, optimizing input layer activations
* W_new = W + dW = W + A.B where A and B are low rank decompositions of the weight update
* Through experiments, authors conclude that it is preferable to adapt more weight matrices (Q, K, V, O) than adapting a single type of weights with a larger rank.
* Interestingly, authors measure subspace similarity to find that lower rank value is sufficient - i.e. increasing r doesn't cover a more meaningful subspace.

References
* [paper](https://arxiv.org/abs/2106.09685)
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