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Study finds post-editing LLM text doesn't fully capture personal style

By PulseAugur Editorial · Summary by gemini-2.5-flash-lite from 2 sources

A study involving 81 participants explored the effectiveness of post-editing large language model (LLM) generated text to match personal writing styles. While post-editing did increase stylistic similarity to the participants' own writing and decrease similarity to raw LLM output, the edited text still retained detectable LLM stylistic traces. Participants often perceived the post-edited text as representative of their personal style, despite quantitative measures showing it remained closer to LLM text than their unassisted writing and exhibited reduced stylistic diversity. AI

Summary written by gemini-2.5-flash-lite from 2 sources. How we write summaries →

IMPACT Post-editing LLM text can align it with personal style, but detectable traces remain, impacting perceived authenticity.

RANK_REASON Academic paper on LLM text post-editing and personal style.

Read on arXiv cs.CL →

COVERAGE [2]

  1. arXiv cs.CL TIER_1 · Connor Baumler, Calvin Bao, Huy Nghiem, Xinchen Yang, Marine Carpuat, Hal Daum\'e III ·

    Can You Make It Sound Like You? Post-Editing LLM-Generated Text for Personal Style

    arXiv:2604.24444v1 Announce Type: new Abstract: Despite the growing use of large language models (LLMs) for writing tasks, users may hesitate to rely on LLMs when personal style is important. Post-editing LLM-generated drafts or translations is a common collaborative writing stra…

  2. arXiv cs.CL TIER_1 · Hal Daumé ·

    Can You Make It Sound Like You? Post-Editing LLM-Generated Text for Personal Style

    Despite the growing use of large language models (LLMs) for writing tasks, users may hesitate to rely on LLMs when personal style is important. Post-editing LLM-generated drafts or translations is a common collaborative writing strategy, but it remains unclear whether users can e…

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