memit-scales-to-10000-edits
IN premise — summaries/2026/08/24/meng-2022-memit-s0-abstract.md
Created 2026-08-25T02:58:12+00:00
MEMIT scales to up to 10,000 simultaneous factual edits in a transformer LM, whereas prior state-of-the-art (SERAC) reached only 75
Summary
MEMIT can correct roughly 10,000 distinct facts in a language model at once without falling apart, while the previous best method could only handle about 75. That is a roughly 133-fold jump, meaning large-scale factual repair becomes practical rather than a laboratory curiosity — you can fix an entire corpus of errors in a single pass instead of needing thousands of separate edits.