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Unno, Y., Ninomiya, T., Miyao, Y. und Tsujii, J., Trimming CFG Parse Trees for Sentence Compression Using Machine Learning Approaches, in: Proceedings of the COLING/ACL 2006 Main Conference Poster Sessions, Seiten 850--857, Association for Computational Linguistics, 2006

Usami, Y., Cho, H. -C., Okazaki, N. und Tsujii, J., Automatic Acquisition of Huge Training Data for Bio-Medical Named Entity Recognition, in: Proceedings of the BioNLP 2011 Workshop, Seiten 65--73, Association for Computational Linguistics, 2011

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Van Landeghem, S., BjÃ¶rne, J., Wei, C-. H, Hakala, K., Pyysalo, S., Ananiadou, S., Kao, H. -Y., Lu, Z., Salakoski, T., Van de Peer, Y. und Ginter, F., Large-scale event extraction from literature with multi-level gene normalization (2013), in: PLOS ONE, 8:4(e55814)

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Vasilakes, J., Georgiadis, P., Nguyen, N. T. H., Miwa, M. und Ananiadou, S., Contextualized Medication Event Extraction with Levitated Markers (2023), in: Journal of Biomedical Informatics(104347)

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Vasilakes, J., Zerva, C. und Ananiadou, S., Subjective Logic Encodings, arXiv, 2025

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Vasilakes, J., Zerva, C., Miwa, M. und Ananiadou, S., Learning Disentangled Representations of Negation and Uncertainty, in: Proceedings of ACL 2022, Seiten 8380–8397, 2022

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Vasquez-Rodriguez, L., Cuenca-Jimenez, P. -M., Morales-Esquivel, S. und Alva-Manchego, F., A Benchmark for Neural Readability Assessment of Texts in Spanish, in: Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022), Seiten 188–198, 2022

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Vasquez-Rodriguez, L., Nguyen, N. T. H., Przybyɫa, P. und Shardlow, M., Simple is not Enough: Document-level Text Simplification using Readability and Coherence, arXiv, 2024

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Vasquez-Rodriguez, L., Nguyen, N. T. H., Shardlow, M. und Ananiadou, S., UoM&MMU at TSAR-2022 Shared Task: Prompt Learning for Lexical Simplification, in: Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022), Seiten 218-224, 2022

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Vasquez-Rodriguez, L., Shardlow, M., Przybyɫa, P. und Ananiadou, S., Investigating Text Simplification Evaluation, in: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, Seiten 876-882, 2021

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Vasquez-Rodriguez, L., Shardlow, M., Przybyɫa, P. und Ananiadou, S., The Role of Text Simplification Operations in Evaluation, in: Proceedings of the First Workshop on Current Trends in Text Simplification (CTTS-2021), Seiten 57-69, 2021

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Venkatesan, A., Kim, J. -H., Talo, F., Ide-Smith, M., Gobeill, J., Carter, J., Batista-Navarro, R., Ananiadou, S., Ruch, P. und McEntyre, J. R., SciLite: a platform for displaying text-mined annotations as a means to link research articles with biological data [version 2; referees: 2 approved, 1 approved with reservations]. (2017), in: Wellcome Open Res, 1:25

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Venturi, G., Montemagni, S., Marchi, S., Sasaki, Y., Thompson, P., McNaught, J. und Ananiadou, S., Bootstrapping a Verb Lexicon for Biomedical Information Extraction, in: Proceedings of the 10th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing 2009), Seiten 137--148, Springer, 2009

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Wang, K., Stevens, R., Alachram, H., Li, Y., Soldatova, L. N., King, R. D., Ananiadou, S., Schoene, A, Li, M., Christopoulou, F., Ambite, J. L., Matthew, J., Garg, S., Hermjakob, U., Marcu, D., Sheng, E., Beissbarth, T., Wingender, E., Galstyan, A., Gao, X., Chambers, B., Pan, W., Khomtchouk, B. B., Evans, J. A. und Rzhetsky, A., NERO: a biomedical named-entity (recognition) ontology with a large, annotated corpus reveals meaningful associations through text embedding (2021), in: npj systems biology and applications, 7(38)

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Wang, X. und Ananiadou, S., A Task-Oriented Extension of the Chinese MeSH Concepts Hierarchy, in: Proceedings of the Second Workshop on Building and Evaluating Resources for Biomedical Text Mining (BioTxtM), LREC 2010, Seiten 23--30, 2010

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Wang, X. und Matthews, M., Distinguishing the species of biomedical named entities for term identification (2008), in: BMC Bioinformatics, 9:Suppl 11(S6)

Wang, X., McKendrick, I., Barrett, I., Dix, I., French, T., Tsujii, J. und Ananiadou, S., Automatic Extraction of Angiogenesis Bio-Process from Text (2011), in: Bioinformatics, 27:19(2730-2737)

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Wang, X., Rak, R., Restificar, A., Nobata, C., Rupp, C. J., Batista-Navarro, R., Nawaz, R. und Ananiadou, S., Detecting Experimental Techniques and Selecting Relevant Documents for Protein-Protein Interactions from Biomedical Literature (2011), in: BMC Bioinformatics, 12:Suppl 8(S11)

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Wang, X., Rak, R., Restificar, A., Nobata, C., Rupp, C. J., Batista-Navarro, R., Nawaz, R. und Ananiadou, S., NaCTeM Systems for BioCreative III PPI Tasks, in: Proceedings of the BioCreative III Workshop, Seiten 142-147, 2010

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Wang, X., Thompson, P. und Ananiadou, S., Biomedical Chinese-English CLIR Using an Extended CMeSH Resource to Expand Queries, in: Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC 2012), Seiten 1148-1155, 2012

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Wang, X., Tsujii, J. und Ananiadou, S., Disambiguating the Species of Biomedical Named Entities Using Natural Language Parsers (2010), in: Bioinformatics, 26:5(661--667)

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Wang, X., Tsujii, J. und Ananiadou, S., Classifying Relations for Biomedical Named Entity Disambiguation, in: Procedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP'09), Seiten 1513--1522, 2009

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Wang, Y., Ananiadou, S. und Tsujii, J., Improve Chinese Clinical Named Entity Recognition Performance by Using the Graphical and Phonetic Feature, in: Proceedings of the 2018 International Workshop on Biomedical and Health Informatics, 2018

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Wang, Y., Fan, X., Chen, L., Chang, E. I-C., Ananiadou, S., Tsujii, J. und Xu, Y., Mapping anatomical related entities to human body parts based on wikipedia in discharge summaries (2019), in: BMC Bioinformatics, 20(430)

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Wang, Y., Feng, D., Dai, Y., Chen, Z., Huang, J., Ananiadou, S., Xie, Q. und Wang, H., HARMONIC: Harnessing LLMs for Tabular Data Synthesis and Privacy Protection, in: Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS), 2024

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