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Gidiotis, A., Tsoumakas, G. (2023) Bayesian Active Summarization. Computer Speech & Language, Vol. 83, pages 101553
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Avramelou, L., Passalis, N., Tsoumakas, G., Tefas, A. (2023) Domain-Specific Large Language Model Finetuning using a Model Assistant for Financial Text Summarization, Proc. 2023 IEEE Symposium Series on Computational Intelligence (SSCI 2023), Mexico City, Mexico.
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Kamtziridis, G., Vrakas, D. & Tsoumakas, G. Does noise affect housing prices? A case study in the urban area of Thessaloniki. EPJ Data Sci. 12, 50 (2023). https://doi.org/10.1140/epjds/s13688-023-00424-3
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B. Liu, J. Wang, K. Sun, G. Tsoumakas (2023), Fine-grained selective similarity integration for drug–target interaction prediction, Briefings in Bioinformatics
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Katsaki, S., Aivazidis, C., Mylonas, N., Mollas, I., Tsoumakas, G. (2023) On the Adaptability of Attention-Based Interpretability in Different Transformer Architectures for Multi-Class Classification Tasks, Proceedings of the AIMLAI Workshop of ECML PKDD 2023.
Bardos, A., Mylonas, N., Mollas, I., Tsoumakas, G. (2023) Local interpretability of random forests for multi-target regression, Proceedings of the AIMLAI Workshop of ECML PKDD 2023.
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Mylonas, N., Mollas, I., Tsoumakas, G. An attention matrix for every decision: faithfulness-based arbitration among multiple attention-based interpretations of transformers in text classification. Data Min Knowl Disc, 38 (1), pp. 128 - 153, 2024.
D. Akrivousis, N. Mylonas, I. Mollas and G. Tsoumakas, "Text classification is keyphrase explainable! Exploring local interpretability of transformer models with keyphrase extraction," 2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA), Thessaloniki, Greece, 2023, pp. 1-9, doi: 10.1109/DSAA60987.2023.10302566.
N. Mylonas, I. Mollas, B. Liu, Y. Manolopoulos and G. Tsoumakas, "On the Persistence of Multilabel Learning, Its Recent Trends, and Its Open Issues," in IEEE Intelligent Systems, vol. 38, no. 2, pp. 28-31, March-April 2023, doi: 10.1109/MIS.2023.3255591.
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Mylonas, N., Karlos, S., & Tsoumakas, G. (2023). WeakMeSH: Leveraging provenance information for weakly supervised classification of biomedical articles with emerging MeSH descriptors. Artificial Intelligence in Medicine, 137, 102505. doi:10.1016/j.artmed.2023.102505
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