GEML: a graph-enhanced pre-trained language model framework for text classification via mutual learning
Author:
Funder
National Natural Science Foundation of China
Education Department of Jilin Province
Department of Science and Technology of Jilin Province
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10489-024-05831-1.pdf
Reference62 articles.
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2. Chen Z, Mao H, Li H et al (2024) Exploring the potential of large language models (llms) in learning on graphs. ACM SIGKDD Explorations Newsl 25(2):42–61
3. Cui H, Wang G, Li Y et al (2022) Self-training method based on GCN for semi-supervised short text classification. Inf Sci 611:18–29
4. Devlin J (2018) Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805
5. Ding K, Wang J, Li J et al (2020) Be more with less: hypergraph attention networks for inductive text classification. In: Conference on empirical methods in natural language processing. pp 4927–4936
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