Ananiadou, S. - NaCTeM Publications - Aigaion 2.0

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Vorname(n):	S.
Nachname(n):	Ananiadou

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SÃ¦tre, R., Kemper, B., Oda, K., Okazaki, N., Matsuoka, Y., Kikuchi, N., Kitano, H., Tsuruoka, Y., Ananiadou, S. und Tsujii, J., PathText: Text Mining Tools Integrated with Biological Pathway, in: Genomes to Systems Conference 2008 Handbook, Seiten 65, The Consortium for Post-Genome Science, 2008

Ohta, T., Pyysalo, S., Ananiadou, S. und Tsujii, J., Pathway Curation Support as an Information Extraction Task, in: Proceedings of the Fourth International Symposium on Languages in Biology and Medicine (LBM 2011), 2011

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Min, E. und Ananiadou, S., PESTO: A Post-User Fusion Network for Rumour Detection on Social Media, in: Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis, Seiten 1-10, 2023

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Zhang, T., Yang, K, Alhuzali, H., Liu, B und Ananiadou, S., PHQ-aware depressive symptoms identification with similarity contrastive learning on social media (2023), in: Information Processing & Management, 60:5(103417)

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Peng, X., Papadopoulos, T., Soufleri, E., Giannouris, P., Xiang, R., Wang, Y., Qian, L., Huang, J., Xie, Q. und Ananiadou, S., Plutus: Benchmarking Large Language Models in Low-Resource Greek Finance, in: Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP), In Press

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Iliopoulos, I., Ananiadou, S., Danchin, A., Ioannidis, J. P. A., Katsikis, P. D., Ouzounis, C. A. und Promponas, V. J., Point of View: Hypothesis, analysis and synthesis, it's all Greek to me (2019), in: eLife, 8(e43514)

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Xie, Q., Bishop, J., Tiwari, P. und Ananiadou, S., Pre-trained language models with domain knowledge for biomedical extractive summarization (2022), in: Knowledge-Based Systems, 252(109460)

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Alhuzali, H., Zhang, T. und Ananiadou, S., Predicting Sign of Depression via Using Frozen Pre-trained Models and Random Forest Classifier., in: CLEF (Working Notes), 2021

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Przybyɫa, P., Brockmeier, A. J., Kontonatsios, G., Le Pogam, M. -A., McNaught, J., von Elm, E., Nolan, K. und Ananiadou, S., Prioritising references for systematic reviews with RobotAnalyst: a user study (2018), in: Research Synthesis Methods, 9:3(470-488)

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Li, M., Nguyen, N. T. H. und Ananiadou, S., Proactive Learning for Named Entity Recognition, in: Proceedings of BioNLP 2017, Seiten 117--125, Association for Computational Linguistics, 2017

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Rak, R., Batista-Navarro, R., Carter, J., Rowley, A. und Ananiadou, S., Processing Biological Literature with Customisable Web Services Supporting Interoperable Formats (2014), in: Database: The Journal of Biological Databases and Curation

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Thompson, P., Kano, Y., McNaught, J., Pettifer, S., Attwood, T. K., Keane, J. und Ananiadou, S., Promoting Interoperability of Resources in META-SHARE, in: Proceedings of the IJCNLP Workshop on Language Resources, Technology and Services in the Sharing Paradigm (LRTS), Seiten 50-58, 2011

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Mu, T., Goulermas, J. Y, Tsujii, J. und Ananiadou, S., Proximity-based Frameworks for Generating Embeddings from Multi-Output Data (2012), in: IEEE Transactions on Pattern Analysis and Machine Intelligence

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Mu, T. und Ananiadou, S., Proximity-based graph embeddings for multi-label classification, in: Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (KDIR 2010), 2010

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BjÃ¶rne, J., Van Landeghem, S., Pyysalo, S., Ohta, T., Ginter, F., Van de Peer, Y., Ananiadou, S. und Salakoski, T., PubMed-Scale Event Extraction for Post-Translational Modifications, Epigenetics and Protein Structural Relations, in: Proceedings of BioNLP 2012, Seiten 82-90, 2012

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Przybyɫa, P., Brockmeier, A. J. und Ananiadou, S., Quantifying Risk Factors in Medical Reports with a Context-Aware Linear Model (2019), in: Journal of the American Medical Informatics Association, 26:6(537â€“546)

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Brockmeier, A. J., Mu, T., Ananiadou, S. und Goulermas, J. Y, Quantifying the Informativeness of Similarity Measurements (2017), in: Journal of Machine Learning Research, 18(1-61)

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Liu, Z., Yang, K, Xie, Q., de Kock, C., Ananiadou, S. und Hovy, E., RAEmoLLM: Retrieval Augmented LLMs for Cross-Domain Misinformation Detection Using In-Context Learning based on Emotional Information, in: Proceedings of ACL 2025, Seiten 16508–16523, 2025

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Luo, Z., Xie, Q. und Ananiadou, S., Readability Controllable Biomedical Document Summarization, in: Findings of the Association for Computational Linguistics: EMNLP 2022, Seiten 4667–4680, 2022

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MihÄƒilÄƒ, C. und Ananiadou, S., Recognising Discourse Causality Triggers in the Biomedical Domain (2013), in: Journal of Bioinformatics and Computational Biology, 11:6(1343008)

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Miwa, M., Thomas, J., O'Mara-Eves, A. und Ananiadou, S., Reducing systematic review workload through certainty-based screening (2014), in: Journal of Biomedical Informatics

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Schoene, A und Ananiadou, S., RELATE: Generating a linguistically inspired Knowledge Graph for fine-grained emotion classification, in: Proceedings of LREC 2022, Seiten 6317-6327, 2022

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Abrar, A., Tabassum Oeshy, N., Kabir, M. und Ananiadou, S., Religious Bias Landscape in Language and Text-to-Image Models: Analysis, Detection, and Debiasing Strategies, arXiv, 2025

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Ji, S., Zhang, T., Yang, K und Ananiadou, S., Rethinking large language models in mental health applications, arXiv, 2023

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Xiao, M., Jiang, Z., Qian, L., Chen, Z., He, Y., Xu, Y., Jiang, Y., Li, D., Weng, R. -L., Peng, M., Huang, J., Ananiadou, S. und Xie, Q., Retrieval-augmented Large Language Models for Financial Time Series Forecasting, arXiv, 2025

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