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

Publikationen von Ananiadou, S. sortiert nach Zeitschrift und Typ
| 1-25 | 26-50 | 51-75 | 76-100 | 101-125 | 126-150 | 151-175 | 176-200 | 201-225 | 226-250 | 251-275 | 276-300 | 301-325 | 326-350 | 351-375 | 376-400 | 401-425 | 426-442 |


Publikationen vom Typ Incollection


2014

Kontonatsios, G., Mihăilă, C., Korkontzelos, I., Thompson, P. und Ananiadou, S., A hybrid approach to compiling bilingual dictionaries of medical terms from parallel corpora, in: Statistical Language and Speech Processing, Second International Conference, SLSP 2014, Seiten 57-69, Springer, 2014
[DOI]
Rosner, M., Attard, A., Thompson, P., Gatt, A. und Ananiadou, S., Extending a Tool Resource Framework with U-Compare, in: Human Language Technology Challenges for Computer Science and Linguistics, Seiten 315-326, Springer, 2014
[URL]

2013

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
[DOI]
[URL]
Batista-Navarro, R., Kontonatsios, G., Mihăilă, 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
[DOI]
[URL]

2012

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

2006

Ananiadou, S. und Nenadić, 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

2005

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
attachment
Nenadić, G., Spasić, I. und Ananiadou, S., Mining Biomedical Abstracts: What’s in a Term?, in: Natural Language Processing – IJCNLP 2004, Springer-Verlag, 2005
attachment

2004

Spasić, I., Nenadić, G. und Ananiadou, S., Learning to Classify Biomedical Terms through Literature Mining and Genetic Algorithms, in: Intelligent Data Engineering and Automated Learning – IDEAL 2004, Seiten 345--351, Springer-Verlag, 2004
attachment

Publikationen vom Typ Inproceedings


2025

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), Seiten 11257–11272, 2025
[DOI]
[URL]
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), Seiten 24–51, 2025
[DOI]
[URL]
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), Seiten 5311 - 5318, 2025
[URL]
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
[URL]
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
[DOI]
[URL]
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
[DOI]
[URL]
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
[URL]
Liu, Z., Zhang, X., Yang, K, Xie, Q., Huang, J. und Ananiadou, S., FMDLlama: Financial Misinformation Detection Based on Large Language Models, in: Proceedings of the ACM on Web Conference 2025, Seiten 1153 - 1157, 2025
[DOI]
[URL]
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, Seiten 18478–18498, 2025
[DOI]
[URL]
Yano, K., Miwa, M. und Ananiadou, S., IRIS: Rapid Curation Framework for Iterative Improvement of Noisy Named Entity Annotations, in: Proceedings of the International Conference on Applications of Natural Language to Information Systems, Seiten 58-69, 2025
[DOI]
[URL]
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, Seiten 7065–7078, 2025
[DOI]
[URL]
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), Seiten 30176–30202, 2025
[DOI]
[URL]
| 1-25 | 26-50 | 51-75 | 76-100 | 101-125 | 126-150 | 151-175 | 176-200 | 201-225 | 226-250 | 251-275 | 276-300 | 301-325 | 326-350 | 351-375 | 376-400 | 401-425 | 426-442 |