Work

Large Language Model Detuning in Learning Content Understanding

Year: 2024

Type: conference-paper

Abstract: In using large language models (LLMs) for education, such as distractors in multiple-choice questions and learning byteaching, error-containing content is used. Prompt tuning and retraining LLMs are possible ways of having LLMs

DOI: 10.33965/celda2024_202408l002

Author: Tsubasa Minematsu and Atsushi Shimada

Language: English

Topic: Intelligent Tutoring Systems and Adaptive Learning

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

OpenAlex ID: W4405074615

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