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All Journal Elementaria: Journal of Educational Research
Gourav Arora
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Religion Humanities Education Languange, Linguistic, Communication & Media Social Sciences

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EcoLLM: A Novel Fine-Tuning Framework for Environmental Sustainability in Large Language Models Gagandeep Singh; Jaskaran Singh; Gourav Arora
Elementaria: Journal of Educational Research Vol. 2 No. 2 (2024): Transformative Learning Approaches
Publisher : Penerbit Hellow Pustaka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61166/elm.v2i2.70

Abstract

The increasing reliance on artificial intelligence (AI) models, such as Large Language Models (LLMs), poses a unique challenge regarding environmental sustainability. Current LLMs prioritize performance and versatility, often neglecting the ecological impact of the solutions they generate. This paper presents a novel approach to fine-tuning LLMs to embed environmental considerations in their responses. By adjusting their training datasets and models, we enhance the likelihood of producing environmentally friendly outcomes. We observed that responses factoring in sustainability increased from 5% to over 75% post-optimization. This paper discusses our methodology, the challenges faced, and the implications for AI’s role in supporting global sustainability goals
Co-Authors Gagandeep Singh Jaskaran Singh