Rank-One Model Editing (ROME) / Linear Associative Memory Editing

Treats an MLP's down-projection weight matrix as a linear associative memory solving W·K≈V, then inserts one new (key, value) association with a minimal closed-form rank-one update — mathematically an outer-product direction mechanism (a whitened key direction detects the trigger, a value direction is written to the output), but the injected value is optimized fresh rather than extracted from any pre-existing linear geometry the model already had for that fact. USES the key-direction/value-injection structure as an editing tool; does not itself claim the edited fact was linearly encoded in the model beforehand.