CLJan 27, 2025

Integration of LLM Quality Assurance into an NLG System

arXiv:2501.16078v1h-index: 5
Originality Synthesis-oriented
AI Analysis

This addresses text quality issues for NLG system users, but it is incremental as it applies an existing LLM method to a new QA task.

The paper tackles the problem of grammar and spelling errors in texts generated by NLG systems by integrating an LLM for quality assurance, and results show it delivers acceptable corrections on sports news texts in three languages.

In this paper, we present a system that uses a Large Language Model (LLM) to perform grammar and spelling correction as a component of Quality Assurance (QA) for texts generated by NLG systems, which is important for text production in real-world scenarios. Evaluating the results of the system on work-in-progress sports news texts in three languages, we show that it is able to deliver acceptable corrections.

Foundations

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