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Detecting online sexual predatory behaviours and abusive language on social media platforms has become a critical area of research due to the growing concerns about online safety, especially for vulnerable populations such as children and adolescents.
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2016
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2019
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2019
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2020
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2020
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A. A. Khan, M. H. Iqbal, S. Nisar, A. Ahmad, and W. Iqbal, “Offensive language detection for low resource language using deep sequence model,” IEEE Transactions on Computational Social Systems , 2023. [Online]. Available: https://doi.org/10.1109/TCSS.2023.3280952
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M. P. Akhter, Z. Jiangbin, I. R. Naqvi, M. AbdelMajeed, and T. Zia, “Abusive language detection from social media comments using conventional machine learning and deep learning approaches,” Multimedia Systems , pp. 1–16, 2021
2021
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2021
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2021
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X. L. Li and P. Liang, “Prefix-tuning: Optimizing continuous prompts for generation,” in Proceedings of the 59th Annual Meeting of the ACL and the 11th International Joint Conference on NLP , vol. 1, 2021, pp. 4582–4597
2021
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B. Lester, R. Al-Rfou, and N. Constant, “The power of scale for parameter-efficient prompt tuning,” in Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing , 2021, pp. 3045–3059
2021
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R. Karimi Mahabadi, J. Henderson, and S. Ruder, “Compacter: Efficient low-rank hypercomplex adapter layers,” Advances in Neural Information Processing Systems , vol. 34, pp. 1022–1035, 2021
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2021
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——, “Detecting sexual predatory chats by perturbed data and balanced ensembles,” in 2021 International Conference of the Biometrics Special Interest Group (BIOSIG) . IEEE, 2021, pp. 1–5
2021
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2023
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2023
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2023
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P. R. Borj, K. Raja, and P. Bours, “Detecting online grooming by simple contrastive chat embeddings,” in Proceedings of the 9th ACM International Workshop on Security and Privacy Analytics , 2023, pp. 57–65
2023
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2023
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2023
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2023
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Q. Zhang, M. Chen, A. Bukharin, P. He, Y. Cheng, W. Chen, and T. Zhao, “Adaptive budget allocation for parameter-efficient fine-tuning,” in The Eleventh International Conference on Learning Representations , 2023. [Online]. Available: https://openreview.net/forum?id=lq62uWRJjiY
2023
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2023
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N. Ding, Y. Qin, G. Yang, F. Wei, Z. Yang, Y. Su, S. Hu, Y. Chen, C.-M. Chan, W. Chen et al. , “Parameter-efficient fine-tuning of large-scale pre-trained language models,” Nature Machine Intelligence , vol. 5, no. 3, pp. 220–235, 2023
2023
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