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Leroi, A. M., Lambert, B. C., Mauch, M., Papadopoulou, M., Ananiadou, S., Lindberg, S. I. I. und Lindenfors, P., On Revolutions (2018), in: V-Dem Working Paper(63)

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Li, M. und Ananiadou, S., Neural Architectures for Aggregating Sequence Labels from Multiple Annotators (2022), in: Neurocomputing

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Li, M., Myrman, A. F., Mu, T. und Ananiadou, S., Modelling Instance-Level Annotator Reliability for Natural Language Labelling Tasks, in: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), Seiten 2873-2883, 2019

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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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Li, M., Takamura, H. und Ananiadou, S., A Neural Model for Aggregating Coreference Annotation in Crowdsourcing, in: Proceedings of the 28th International Conference on Computational Linguistics (COLING 2020), Seiten 5760-5773, 2020

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Liakata, M., Thompson, P., de Waard, A., Nawaz, R., Pander Maat, H. und Ananiadou, S., A three-way perspective on scientiï¬c discourse annotation for knowledge extraction, in: Proceedings of the ACL Workshop on Detecting Structure in Scholarly Discourse (DSSD), Seiten 37-46, 2012

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Liu, B, Schlegel, V., Batista-Navarro, R. und Ananiadou, S., Entity Coreference and Co-occurrence Aware Argument Mining from Biomedical Literature, in: Proceedings of the 4th Workshop on Computational Approaches to Discourse (CODI 2023, 2023

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Liu, B, Schlegel, V., Batista-Navarro, R. und Ananiadou, S., Argument mining as a multi-hop generative machine reading comprehension task, in: Findings of the Association for Computational Linguistics: EMNLP 2023, Seiten 10846–10858, 2023

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Liu, B, Schlegel, V., Batista-Navarro, R. und Ananiadou, S., Incorporating Zoning Information into Argument Mining from Biomedical Literature, in: Proceedings of LREC 2022, Seiten 6162-6169, 2022

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Liu, B, Schlegel, V., Thompson, P., Batista-Navarro, R. und Ananiadou, S., Global information-aware argument mining based on a top-down multi-turn QA model (2023), in: Information Processing & Management, 60:5(103445)

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Liu, Z., Liu, B, Thompson, P., Yang, K und Ananiadou, S., ConspEmoLLM: Conspiracy Theory Detection Using an Emotion-Based Large Language Model, in: Proceedings of the 13th International Conference on Prestigious Applications of Intelligent Systems (PAIS-2024), 2024

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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, arXiv, 2024

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Liu, Z., Yang, K, Zhang, T., Xie, Q., Yu, Z. und Ananiadou, S., EmoLLMs: A Series of Emotional Large Language Models and Annotation Tools for Comprehensive Affective Analysis, in: Proceedings of KDD 2024, Seiten 5487 - 5496, 2024

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Liu, Z., Zhang, T., Yang, K, Thompson, P., Yu, Z. und Ananiadou, S., Emotion detection for misinformation: A review (2024), in: Information Fusion, 107(102300)

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Liu, Z., Zhang, X., Yang, K, Xie, Q., Huang, J. und Ananiadou, S., FMDLlama: Financial Misinformation Detection based on Large Language Models, arXiv, 2024

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Luo, Z., Liu, L., Ananiadou, S. und Xie, Q., Graph Contrastive Topic Model (2024), in: Expert Systems with Applications, 255:Part C(124631)

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Luo, Z., Xie, Q. und Ananiadou, S., The Lay Person’s Guide to Biomedicine: Orchestrating Large Language Models, arXiv, 2024

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Luo, Z., Xie, Q. und Ananiadou, S., Factual consistency evaluation of summarization in the Era of large language models (2024), in: Expert Systems with Applications, 254(124456)

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Luo, Z., Xie, Q. und Ananiadou, S., CitationSum: Citation-aware Graph Contrastive Learning for Scientific Paper Summarization, in: Proceedings of the ACM Web Conference, Seiten 1843–1852, 2023

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Luo, Z., Xie, Q. und Ananiadou, S., ChatGPT as a Factual Inconsistency Evaluator for Text Summarization, arXiv, 2023

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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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Luo, Z., Yuan, C., Xie, Q. und Ananiadou, S., Are Large Language Models True Healthcare Jacks-of-All-Trades? Benchmarking Across Health Professions Beyond Physician Exams, arXiv, 2024

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Lyte, V., Jones, S., Ananiadou, S. und Kerr, L., UK Institutional Repository Search: Innovation and Discovery (2009), in: Ariadne, 61

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Matsubayashi, Y., Okazaki, N. und Tsujii, J., A Comparative Study on Generalization of Semantic Roles in FrameNet., in: Proceedings of ACL-IJCNLP 2009, Seiten 19--27, 2009

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Matsubayashi, Y., Okazaki, N. und Tsujii, J., Accurate and Robust Semantic Role Labeling using Multiple Generalization Criteria in PropBank, in: Proceedings of the 5th International Conference on Generative Approaches to the Lexicon, Seiten 97--104, 2009

| 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 | 426-450 | 451-475 | 476-500 | 501-525 | 526-546 |

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