Work

Research on Fine-Tuning and Prompt Engineering of LLMs for Scientific Literature in Power Grid

Year: 2025

Type: conference-paper

Source: International Conference on Artificial Intelligence, Big Data and Algorithms (CAIBDA)

DOI: 10.1109/caibda65784.2025.11182770

Authors: Min Hua, Qiyu Lu, Bin Hua, Ping Song, Ling Luo

Institution: State Grid Shanghai Municipal Electric Power Company (China)

Language: English

Topic: Topic Modeling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: closed

OpenAlex ID: W4415003343

FWCI:

Cites: 10

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