  We introduce CoEdIT, a state-of-the-art text editing system for writing
assistance. CoEdIT takes instructions from the user specifying the attributes
of the desired text, such as "Make the sentence simpler" or "Write it in a more
neutral style," and outputs the edited text. We present a large language model
fine-tuned on a diverse collection of task-specific instructions for text
editing (a total of 82K instructions). Our model (1) achieves state-of-the-art
performance on various text editing benchmarks, (2) is competitive with
publicly available largest-sized LLMs trained on instructions while being
nearly 60x smaller, (3) is capable of generalizing to unseen edit instructions,
and (4) exhibits abilities to generalize to composite instructions containing
different combinations of edit actions. Through extensive qualitative and
quantitative analysis, we show that writers prefer the edits suggested by
CoEdIT relative to other state-of-the-art text editing models. Our code, data,
and models are publicly available at https://github.com/vipulraheja/coedit.
