APIO: Automatic Prompt Induction and Optimization for Grammatical Error Correction and Text Simplification

• URL: http://arxiv.org/abs/2508.09378v1
• Date: Tue, 12 Aug 2025 22:26:32 GMT
• Title: APIO: Automatic Prompt Induction and Optimization for Grammatical Error Correction and Text Simplification
• Authors: Artem Chernodub, Aman Saini, Yejin Huh, Vivek Kulkarni, Vipul Raheja,
• Abstract summary: APIO is a simple but effective prompt induction and optimization approach for the tasks of Grammatical Error Correction (GEC) and Text Simplification.<n>We make our data, code, prompts, and outputs publicly available.
• Score: 5.756837532779593
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Recent advancements in large language models (LLMs) have enabled a wide range of natural language processing (NLP) tasks to be performed through simple prompt-based interactions. Consequently, several approaches have been proposed to engineer prompts that most effectively enable LLMs to perform a given task (e.g., chain-of-thought prompting). In settings with a well-defined metric to optimize model performance, automatic prompt optimization (APO) methods have been developed to refine a seed prompt. Advancing this line of research, we propose APIO, a simple but effective prompt induction and optimization approach for the tasks of Grammatical Error Correction (GEC) and Text Simplification, without relying on manually specified seed prompts. APIO achieves a new state-of-the-art performance for purely LLM-based prompting methods on these tasks. We make our data, code, prompts, and outputs publicly available.

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