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Abstract

Recent advancements in natural language generation (NLG) have revolutionized content creation, enabling artificial intelligence (AI) tools to produce coherent and seemingly authentic texts, including scholarly papers. While AI-generated content offers efficiencies in speed and volume, concerns over authenticity, ethical implications, and academic integrity persist. This review explores methods and considerations for identifying AI-generated research papers, emphasizing the need to distinguish between human-authored and AI-generated content to uphold scholarly standards and ensure transparency in research. Key detection techniques include textual analysis, metadata examination, and content evaluation. Ethical concerns regarding AI's role in research are also discussed, underscoring the importance of ongoing research to refine identification methodologies and maintain research integrity.

Keywords

Artificial Intelligence Natural Language Generation AI-Generated Content Scholarly Publishing Research Integrity Textual Analysis Metadata Examination Ethical Considerations

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Willie, M. M. . (2024). Identifying AI-Generated Research Papers: Methods and Considerations: Methods and Considerations. Golden Ratio of Data in Summary, 4(2), 736–739. https://doi.org/10.52970/grdis.v4i2.489
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References

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