ReFT: Representation Finetuning for Language Models

Parameter-efficient finetuning (PEFT) methods seek to adapt large neural models via updates to a small number of . However, much prior interpretability work has shown that encode rich semantic information, suggesting that editing representations might be a more powerful alternative.