Weird Generalization and Inductive Backdoors: New Ways to Corrupt LLMs

Jan Betley, Jorio Cocola, Dylan Feng +4

LLMs are useful because they generalize so well. But can you have too much of a good thing? We show that a small amount of finetuning in narrow contexts can dramatically shift beha…