mend-hypernetwork-approach
IN premise — summaries/2026/08/24/zhong-2023-mquake-s4-mq-uake-challenges-model-editors.md
Created 2026-08-25T02:59:05+00:00
MEND trains a hypernetwork to produce weight updates from raw fine-tuning gradients for each edited fact
Summary
Instead of running a slow fine-tuning loop every time a fact needs to be edited, MEND learns a small generator network that predicts the right weight adjustments from a quick gradient readout. The practical upshot is that model editing becomes a fast, one-shot lookup rather than an expensive optimization, making per-fact updates much cheaper to perform.