Ananiadou, S. - NaCTeM Publications - Aigaion 2.0

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

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Dwivedi, Y. K., Hughes, L., Bhadeshia, H. K. D. H., Ananiadou, S., Cohn, A. G., Cole, J. M., Conduit, G. J., Desarkar, M. S. and Wang, X., Artificial intelligence (AI) futures: India-UK collaborations emerging from the 4th Royal Society Yusuf Hamied workshop (2024), in: International Journal of Information Management(102725)

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Yuan, C., Xie, Q., Huang, J. and 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), páginas 1963 - 1974, 2024

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Bishop, J., Xie, Q. and Ananiadou, S., LongDocFACTScore: Evaluating the Factuality of Long Document Abstractive Summarisation, in: Proceedings of LREC-COLING 2024, páginas 10777-10789, 2024

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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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Xie, Q., Tiwari, P. and Ananiadou, S., Knowledge-enhanced Graph Topic Transformer for Explainable Biomedical Text Summarization (2023), in: IEEE Journal of Biomedical and Health Informatics

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Min, E. and Ananiadou, S., PESTO: A Post-User Fusion Network for Rumour Detection on Social Media, in: Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis, páginas 1-10, 2023

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Yang, K, Zhang, T. and Ananiadou, S., Disentangled Variational Autoencoder for Emotion Recognition in Conversations (2023), in: IEEE Transactions on Affective Computing(1-12)

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Ji, S., Zhang, T., Yang, K and Ananiadou, S., Domain-specific Continued Pretraining of Language Models for Capturing Long Context in Mental Health, arXiv, 2023

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Xie, Q., Luo, Z. and Ananiadou, S., A Survey for Biomedical Text Summarization: From Pre-trained to Large Language Models, arXiv, 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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Yang, K, Ji, S., Zhang, T., Xie, Q., Kuang, Z. and Ananiadou, S., Towards Interpretable Mental Health Analysis with Large Language Models, in: Proceedings of EMNLP 2023, páginas 6056–6077, 2023

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Yang, K, Zhang, T. and Ananiadou, S., A Bipartite Graph is All We Need for Enhancing Emotional Reasoning with Commonsense Knowledge, in: Proceedings of CIKM 2023, páginas 2917–2927, 2023

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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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Goldsack, T., Luo, Z., Xie, Q., Scarton, C., Shardlow, M., Ananiadou, S. and Lin, C., BioLaySumm 2023 Shared Task: Lay Summarisation of Biomedical Research Articles, in: Proceedings of BioNLP 2023, páginas 468–477, 2023

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Miwa, M. and Ananiadou, S., DISTANT: Distantly Supervised Entity Span Detection and Classification, in: Proceedings of BioNLP 2023, páginas 171–177, 2023

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Yuan, C., Xie, Q. and Ananiadou, S., Zero-shot Temporal Relation Extraction with ChatGPT, in: Proceedings of BioNLP 2023, páginas 92–102, 2023

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Cao, J., Peek, N., Renehan, A. G and Ananiadou, S., Gaussian Distributed Prototypical Network for Few-shot Genomic Variant Detection, in: Proceedings of BioNLP 2023, páginas 26–36, 2023

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Zhang, T., Yang, K and Ananiadou, S., Sentiment-guided Transformer with Severity-aware Contrastive Learning for Depression Detection on Social Media, in: Proceedings of BioNLP 2023, páginas 114–126, 2023

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Zhang, T., Yang, K, Alhuzali, H., Liu, B and Ananiadou, S., PHQ-aware depressive symptoms identification with similarity contrastive learning on social media (2023), in: Information Processing & Management, 60:5(103417)

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

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Xie, Q., Huang, J., Saha, T and Ananiadou, S., GRETEL: Graph Contrastive Topic Enhanced Language Model for Long Document Extractive Summarization, in: Proceedings of COLING, páginas 6259–6269, 2022

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Alhuzali, H., Zhang, T. and Ananiadou, S., Emotions and Topics Expressed on Twitter During the COVID-19 Pandemic in the United Kingdom: Comparative Geolocation and Text Mining Analysis (2022), in: Journal of Medical Internet Research, 24:10(e40323)

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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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Cao, J., van Veen, E. M., Peek, N., Renehan, A. G and Ananiadou, S., A Novel Automated Approach to Mutation-Cancer Relation Extraction by Incorporating Heterogeneous Knowledge (2023), in: IEEE Journal of Biomedical and Health Informatics, 27:2(1096 - 1105)

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Schoene, A, Bojanic, L., Nghiem, M-. Q., Hunt, I. M. and Ananiadou, S., Classifying suicide-related content and emotions on Twitter using Graph Convolutional Neural Networks (2022), in: IEEE Transactions on Affective Computing(1-12)

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