Generation and Validation of Teaching Examples Based on Large Language Models

被引:2
作者
He, Qing [1 ]
Wang, Yu [1 ]
Rao, Gaoqi [1 ]
机构
[1] Beijing Language & Culture Univ, Beijing, Peoples R China
来源
2024 INTERNATIONAL CONFERENCE ON ASIAN LANGUAGE PROCESSING, IALP 2024 | 2024年
关键词
Large Language Model; Example Sentence Generation; Coarse Processing; Fine Processing; Validation Standards;
D O I
10.1109/IALP63756.2024.10661177
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Example sentences serve as a crucial bridge for learners to master language application rules, enhance language skills, and develop a sense of language. These sentences encompass various aspects, including semantics, grammar, and pragmatics, and hold significant importance in the fields of language teaching and publishing. Large Language Model (LLM) have facilitated the construction and development of generative corpora. Empowered by LLM, example sentences are linked with linguistic elements such as parts of speech and meanings. During the generation process, both coarse-grained and fine-grained resources are fully utilized; in the screening process, relevant research findings on example sentences, errors, and corrections are extensively referenced to form screening norms. This approach results in the construction of a generative example sentence corpus that meets educational needs and maintains a high degree of standardization.
引用
收藏
页码:389 / 395
页数:7
相关论文
共 50 条
  • [21] A comprehensive survey of large language models and multimodal large models in medicine
    Xiao, Hanguang
    Zhou, Feizhong
    Liu, Xingyue
    Liu, Tianqi
    Li, Zhipeng
    Liu, Xin
    Huang, Xiaoxuan
    INFORMATION FUSION, 2025, 117
  • [22] Data augmentation based on large language models for radiological report classification
    Collado-Montanez, Jaime
    Martin-Valdivia, Maria-Teresa
    Martinez-Camara, Eugenio
    KNOWLEDGE-BASED SYSTEMS, 2025, 308
  • [23] Chart Question Answering based on Modality Conversion and Large Language Models
    Liu, Yi-Cheng
    Chu, Wei-Ta
    PROCEEDINGS OF THE FIRST ACM WORKSHOP ON AI-POWERED QUESTION ANSWERING SYSTEMS FOR MULTIMEDIA, AIQAM 2024, 2024, : 19 - 24
  • [24] Editing Personality For Large Language Models
    Mao, Shengyu
    Wang, Xiaohan
    Wang, Mengru
    Jiang, Yong
    Xie, Pengjun
    Huang, Fei
    Zhang, Ningyu
    NATURAL LANGUAGE PROCESSING AND CHINESE COMPUTING, PT II, NLPCC 2024, 2025, 15360 : 241 - 254
  • [25] A survey of multilingual large language models
    Qin, Libo
    Chen, Qiguang
    Zhou, Yuhang
    Chen, Zhi
    Li, Yinghui
    Liao, Lizi
    Li, Min
    Che, Wanxiang
    Yu, Philip S.
    PATTERNS, 2025, 6 (01):
  • [26] A survey on multimodal large language models
    Yin, Shukang
    Fu, Chaoyou
    Zhao, Sirui
    Li, Ke
    Sun, Xing
    Xu, Tong
    Chen, Enhong
    NATIONAL SCIENCE REVIEW, 2024, 11 (12)
  • [27] Large Language Models: A Guide for Radiologists
    Kim, Sunkyu
    Lee, Choong-kun
    Kim, Seung-seob
    KOREAN JOURNAL OF RADIOLOGY, 2024, 25 (02) : 126 - 133
  • [28] Large Language Models in Cosmetic Dermatology
    Landau, Marina
    Kroumpouzos, George
    Goldust, Mohamad
    JOURNAL OF COSMETIC DERMATOLOGY, 2025, 24 (02)
  • [29] Consumer segmentation with large language models
    Li, Yinan
    Liu, Ying
    Yu, Muran
    JOURNAL OF RETAILING AND CONSUMER SERVICES, 2025, 82
  • [30] Applications of Large Language Models in Pathology
    Cheng, Jerome
    BIOENGINEERING-BASEL, 2024, 11 (04):