Rumor Detection with Supervised Graph Contrastive Regularization
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-8184-7_13
Reference22 articles.
1. Bardes, A., Ponce, J., LeCun, Y.: VICReg: variance-invariance-covariance regularization for self-supervised learning (2021). https://doi.org/10.48550/ARXIV.2105.04906, https://arxiv.org/abs/2105.04906
2. Bian, T., et al.: Rumor detection on social media with bi-directional graph convolutional networks (2020)
3. Dou, Y., Shu, K., Xia, C., Yu, P.S., Sun, L.: User preference-aware fake news detection. In: Proceedings of the 44nd International ACM SIGIR Conference on Research and Development in Information Retrieval (2021)
4. Han, Y., Karunasekera, S., Leckie, C.: Graph neural networks with continual learning for fake news detection from social media. CoRR abs/2007.03316 (2020)
5. Khosla, P., et al.: Supervised contrastive learning. Adv. Neural. Inf. Process. Syst. 33, 18661–18673 (2020)
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