Towards Human-Like Educational Question Generation with Small Language Models

被引：1

作者：

Fawzi, Fares ^{[1
]}

Balan, Sarang ^{[1
]}

Cukurova, Mutlu ^{[1
]}

Yilmaz, Emine ^{[1
]}

Bulathwela, Sahan ^{[1
]}

机构：

[1] UCL, London, England

来源：

ARTIFICIAL INTELLIGENCE IN EDUCATION: POSTERS AND LATE BREAKING RESULTS, WORKSHOPS AND TUTORIALS, INDUSTRY AND INNOVATION TRACKS, PRACTITIONERS, DOCTORAL CONSORTIUM AND BLUE SKY, AIED 2024, PT I | 2024年 / 2150卷

关键词：

Question Generation; AI in Education; small Language Models;

D O I：

10.1007/978-3-031-64315-6_25

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

With the advent of Generative AI models, the automatic generation of educational questions plays a key role in developing online education. This work compares large-language model-based (LLM) systems and their small-language model (sLM) counterparts for educational question generation. Our experiments, quantitatively and qualitatively, demonstrate that sLMs can produce educational questions with comparable quality by further pre-training and fine-tuning.

引用

页码：295 / 303

页数：9

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