Ananiadou, S. - NaCTeM Publications

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

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Ananiadou, S., Thompson, P. und Nawaz, R., Enhancing Search: Events and their Discourse Context, in: Computational Linguistics and Intelligent Text Processing, Seiten 318-334, Springer, 2013

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Batista-Navarro, R., Kontonatsios, G., MihÄƒilÄƒ, C., Thompson, P., Rak, R., Nawaz, R., Korkontzelos, I. und Ananiadou, S., Facilitating the Analysis of Discourse Phenomena in an Interoperable NLP Platform, in: Computational Linguistics and Intelligent Text Processing, Seiten 559-571, Springer Berlin Heidelberg, 2013

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Ananiadou, S., McNaught, J. und Thompson, P., The English Language in the Digital Age, in: White Paper Series, Springer, 2012

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Ananiadou, S. und NenadiÄ‡, G., Automatic Terminology Management in Biomedicine, in: Text Mining for Biology and Biomedicine, Seiten 67--98, Artech House, Inc., 2006

Kim, J.-D. und Tsujii, J., Corpora and their Annotation, in: Text Mining for Biology and Biomedicine, Artech House, 2006

Ananiadou, S. und McNaught, J., Introduction to Text Mining in Biology, in: Text Mining for Biology and Biomedicine, Seiten 1--12, Artech House, Inc., 2006

Tsuruoka, Y., Tateisi, Y., Kim, J.-D., Ohta, T., McNaught, J., Ananiadou, S. und Tsujii, J., Developing a Robust Part-of-Speech Tagger for Biomedical Text, in: Advances in Informatics - 10th Panhellenic Conference on Informatics, Seiten 382--392, Springer-Verlag, 2005

NenadiÄ‡, G., SpasiÄ‡, I. und Ananiadou, S., Mining Biomedical Abstracts: Whatâ€™s in a Term?, in: Natural Language Processing â€“ IJCNLP 2004, Springer-Verlag, 2005

SpasiÄ‡, I., NenadiÄ‡, G. und Ananiadou, S., Learning to Classify Biomedical Terms through Literature Mining and Genetic Algorithms, in: Intelligent Data Engineering and Automated Learning â€“ IDEAL 2004, Seiten 345--351, Springer-Verlag, 2004

Yu, Z., Belinkov, Y. und Ananiadou, S., Back Attention: Understanding and Enhancing Multi-Hop Reasoning in Large Language Models, in: Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP), In Press

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Kabir, M., Abrar, A. und Ananiadou, S., Break the Checkbox: Challenging Closed-Style Evaluations of Cultural Alignment in LLMs, in: Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP), In Press

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Liu, Z., Thompson, P., Rong, J. und Ananiadou, S., ConspEmoLLM-v2: A robust and stable model to detect sentiment-transformed conspiracy theories, in: Proceedings of the 14th Conference on Prestigious Applications of Intelligent Systems (PAIS-2025), In Press

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Kabir, M., Tahsin, T. und Ananiadou, S., From n-gram to Attention: How Model Architectures Learn and Propagate Bias in Language Modelin, in: Findings of the Association for Computational Linguistics: EMNLP 2025, In Press

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Yu, Z. und Ananiadou, S., Locate-then-Merge: Neuron-Level Parameter Fusion for Mitigating Catastrophic Forgetting in Multimodal LLMs, in: Findings of the Association for Computational Linguistics: EMNLP 2024, In Press

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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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Yang, K, Liu, Z., Xie, Q., Huang, J., Min, E. und Ananiadou, S., Selective Preference Optimization via Token-Level Reward Function Estimation, in: Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP), In Press

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Zhang, X., Wei, Q., Zhu, Y., Wu, F. und Ananiadou, S., THCM-CAL: Temporal-Hierarchical Causal Modelling with Conformal Calibration for Clinical Risk Prediction, in: Findings of the Association for Computational Linguistics: EMNLP 2024, In Press

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Yano, K., Luo, Z., Huang, J., Xie, Q., Asada, M., Yuan, C., Yang, K, Miwa, M., Ananiadou, S. und Tsujii, J., ELAINE-medLLM: Lightweight English Japanese Chinese Trilingual Large Language Model for Bio-medical Domain, in: Proceedings of the 31st International Conference on Computational Linguistics (COLING 2025), Seiten 4670–4688, 2025

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Luo, Z., Yuan, C., Xie, Q. und Ananiadou, S., EMPEC: A Comprehensive Benchmark for Evaluating Large Language Models Across Diverse Healthcare Professions, in: Findings of the Association for Computational Linguistics: ACL 2025, Seiten 9945–9958, 2025

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Soufleri, E. und Ananiadou, S., Enhancing Stress Detection on Social Media Through Multi-Modal Fusion of Text and Synthesized Visuals, in: Proceedings of the 24th Workshop on Biomedical Language Processing (BioNLP), Seiten 34–43, 2025

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Liu, Z., Wang, K., Bao, Z., Zhang, X., Dong, J., Yang, K, Kabir, M., Giannouris, P., Xing, R., Park, S., Kim, J., Li, D., Xie, Q. und Ananiadou, S., FinNLP-FNP-LLMFinLegal-2025 Shared Task: Financial Misinformation Detection Challenge Task, in: Proceedings of the Joint Workshop of the 9th Financial Technology and Natural Language Processing (FinNLP), the 6th Financial Narrative Processing (FNP), and the 1st Workshop on Large Language Models for Finance and Legal (LLMFinLegal), Seiten 271–276, 2025

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Xiong, G., Deng, Z., Wang, K., Cao, Y., Li, H., Yu, Y., Peng, X., Lin, M., Smith, K., Liu, X. -Y., Huang, J., Ananiadou, S. und Xie, Q., FLAG-Trader: Fusion LLM-Agent with Gradient-based Reinforcement Learning for Financial Trading, in: Findings of the Association for Computational Linguistics: ACL 2025, Seiten 13921–13934, 2025

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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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Zhang, X., Wei, Q., Zhu, Y., Zhang, L., Zhou, D. und Ananiadou, S., SynGraph: A Dynamic Graph-LLM Synthesis Framework for Sparse Streaming User Sentiment Modeling, in: Findings of the Association for Computational Linguistics: ACL 2025, Seiten 16338–16356, 2025

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Yuan, C., Xie, Q., Huang, J. und Ananiadou, S., Back to the Future: Towards Explainable Temporal Reasoning with Large Language Models, in: Proceedings of the ACM on Web Conference 2024 (WWW '24), Seiten 1963 - 1974, 2024

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