Small Is Enough: Per-User Style Rewriting of AI-Edited Text via LoRA Adapters

2026-07-31

AI Summary

This work proposes a privacy-preserving, instruction-free approach to personalized text rewriting that achieves style transfer using only a user’s own documents, eliminating the need for in-context prompting during inference. The method leverages multiple local auxiliary large language models to construct training pairs, fine-tunes base models ranging from 0.5B to 7B parameters via LoRA, and incorporates automatic text chunking with length-aware generation. Evaluation on 219 scientific paper rewriting pairs reveals a performance plateau at an automatic composite score of 0.69, indicating that even small models are sufficiently effective. Human evaluations by LLM judges show an average reduction of over 20% in perceived “AI-ness” of outputs, which further decreases with larger model scales. This study is the first to demonstrate a scaling saturation effect in this task, validating the efficacy and practicality of lightweight, single-user adaptation frameworks.

Abstract

InMyStyle is a privacy first, single user system that adapts small language models to rewrite AI-edited text towards an individual user's writing style without an instruction prompt at inference. Given a user's documents, it uses multiple local helper LLMs to construct paired training examples and fine tunes LoRA adapters on base models ranging from 0.5B to 7B parameters. Length aware generation budgets and automatic chunking support inputs of different lengths. On 219 evaluation pairs from a scientific-paper corpus, the automatic composite score plateaus at 0.69 [scale 0-1] across all model sizes under both greedy and sampled decoding. This observed plateau suggests that small models are sufficient for the measured rewriting task, with model size determining trade-offs rather than a stable quality ranking. As a secondary evaluation, 400 ratings from five LLM judges give InMyStyle outputs a mean perceived AI-ness score over 20% lower than their helper-AI generated inputs, while mean perceived AI-ness scores decrease with model size within InMyStyle.

Problem

• personalized rewriting
• writing style adaptation
• AI-edited text
• privacy-preserving
• single-user system

Innovation

• LoRA adapters
• style rewriting
• small language models
• privacy-preserving personalization
• length-aware generation