Update README.md

README.md

@@ -95,6 +95,14 @@ whereas the general (non-orthogonal) "multiplicative-LoRA" method can (in theory
 
 `h' = h + u @ v^T @ h`
 
+It can also (in theory) perform [Householder Transformation(s)](https://en.wikipedia.org/wiki/Householder_transformation):
+
+`h' = h - 2 * v @ v^T @ h`
+
+by choosing to set `u = -2v` like so:
+
+`h' = h + u @ v^T @ h`
+
 In general, the way to think about these (non-orthogonal) "multiplicative-LoRAs" is as a kind of "conditional control-vector":
 
 - Each vector in `lora_A` looks for a certain dirrection, and via the dot-product it generates a (signed) weighting factor that measures the similarity between the output of the `down_proj` transformation and the specific vector in `lora_A`.