Ananiadou, S. - NaCTeM Publications

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Primeiro nome(s):	S.
Sobrenome(s):	Ananiadou

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Li, M., Myrman, A. F., Mu, T. and 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), páginas 2873-2883, 2019

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

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

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Liakata, M., Thompson, P., de Waard, A., Nawaz, R., Pander Maat, H. and 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), páginas 37-46, 2012

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

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

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Liu, B, Schlegel, V., Thompson, P., Batista-Navarro, R. and 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 and 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), páginas 4649 - 4656, 2024

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Liu, Z., Qian, L., Xie, Q., Huang, J., Yang, K and Ananiadou, S., MMAFFBen: A Multilingual and Multimodal Affective Analysis Benchmark for Evaluating LLMs and VLMs, arXiv, 2025

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Liu, Z., Thompson, P., Rong, J. and 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), páginas 5311 - 5318, 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. and 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), páginas 271–276, 2025

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Liu, Z., Yang, K, Hovy, E. and Ananiadou, S., Rumor Detection by Multi-task Suffix Learning based on Time-series Dual Sentiments, arXiv, 2025

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

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

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Liu, Z., Zhang, T., Yang, K, Thompson, P., Yu, Z. and 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. and Ananiadou, S., FMDLlama: Financial Misinformation Detection Based on Large Language Models, in: Proceedings of the ACM on Web Conference 2025, páginas 1153 - 1157, 2025

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

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

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

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

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

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

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Luo, Z., Yuan, C., Xie, Q. and 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, páginas 9945–9958, 2025

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