Ananiadou, S. - NaCTeM Publications - Aigaion 2.0

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

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Wang, Y., Fan, X., Chen, L., Chang, E. I-C., Ananiadou, S., Tsujii, J. and 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. and 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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Williams, J., Matragkas, N., Kolovos, D. S., Korkontzelos, I., Ananiadou, S. and Paige, R. F., Software Analytics for MDE Communities, in: Proceedings of the Open Source Software for Model Driven Engineering Workshop (OSS4MDEâ€™14), 2014

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Xiao, M., Jiang, Z., Qian, L., Chen, Z., He, Y., Xu, Y., Jiang, Y., Li, D., Weng, R. -L., Peng, M., Huang, J., Ananiadou, S. and Xie, Q., Retrieval-augmented Large Language Models for Financial Time Series Forecasting, arXiv, 2025

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Xie, Q., Bishop, J., Tiwari, P. and Ananiadou, S., Pre-trained language models with domain knowledge for biomedical extractive summarization (2022), in: Knowledge-Based Systems, 252(109460)

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Xie, Q., Han, W., Chen, Z., Xiang, R., Zhang, X., He, Y., Xiao, M., Li, D., Dai, Y., Feng, D., Xu, Y., Kang, H., Kuang, Z., Yuan, C., Yang, K, Luo, Z., Zhang, T., Liu, Z., Xiong, G., Deng, Z., Jiang, Y., Yao, Z., Li, H., Yu, Y., Lopez-Lira, A., Wang, B., Lai, Y., Wang, H., Peng, M., Ananiadou, S. and Huang, J., FinBen: An Holistic Financial Benchmark for Large Language Models, in: Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS), 2024

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Xie, Q., Huang, J., Li, D., Chen, Z., Xiang, R., Xiao, M., Yu, Y., Somasundaram, V., Yang, K, Yuan, C., Luo, Z., Liu, Z., He, Y., Jiang, Y., Li, H., Feng, D., Liu, X. -Y., Wang, B., Wang, H., Lai, Y., Suchow, J., Lopez-Lira, A., Peng, M. and Ananiadou, S., FinNLP-AgentScen-2024 Shared Task: Financial Challenges in Large Language Models - FinLLMs, in: Proceedings of the Eighth Financial Technology and Natural Language Processing and the 1st Agent AI for Scenario Planning, páginas 119- 126, 2024

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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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Xie, Q., Li, D., Xiao, M., Jiang, Y., Xiang, R., Zhang, X., Chen, Z., He, Y., Han, W., Yang, Y., Chen, S., Zhang, Y., Shen, L., Kim, D., Liu, Z., Luo, Z., Yu, Y., Cao, Y., Deng, Z., Yao, Z., Li, H., Feng, D., Dai, Y., Somasundaram, V., Lu, P., Zhao, Y., Long, Y., Xiong, G., Smith, K., Yu, H., Lai, Y., Peng, M., Nie, J., Suchow, J., Liu, X. -Y., Wang, B., Lopez-Lira, A., Huang, J. and Ananiadou, S., Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications, arXiv, 2024

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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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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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Xiong, G., Deng, Z., Wang, K., Cao, Y., Li, H., Yu, Y., Peng, X., Lin, M., Smith, K., Liu, X. -Y., Huang, J., Ananiadou, S. and Xie, Q., FLAG-Trader: Fusion LLM-Agent with Gradient-based Reinforcement Learning for Financial Trading, in: Findings of the Association for Computational Linguistics: ACL 2025, páginas 13921–13934, 2025

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Xu, B., Liu, Z. and Ananiadou, S., Disentangled VAD Representations via a Variational Framework for Political Stance Detection, arXiv, 2025

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Xu, Y., Chen, L., Wei, J., Ananiadou, S., Fan, Y., Qian, Y., Chang, E. I-C. and Tsujii, J., Bilingual term alignment from comparable corpora in English discharge summary and Chinese discharge summary (2015), in: BMC Bioinformatics, 16(149)

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Xu, Y., Hua, J., Ni, Z., Chen, Q., Fan, Y., Ananiadou, S., Chang, E. I-C. and Tsujii, J., Anatomical entity recognition with a hierarchical framework augmented by external resources (2014), in: PLOS ONE, 9:10(e108396)

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Yamada, T., Kamata, R., Ishinohachi, K., Shojima, N., Ananiadou, S., Noma, H., Yamauchi, T. and Kadowaki, T., Biosimilar Versus Originator Insulins: Systematic review and meta-analysis (2018), in: Diabetes, Obesity and Metabolism

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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, Liu, Z., Xie, Q., Huang, J., Min, E. and Ananiadou, S., Selective Preference Optimization via Token-Level Reward Function Estimation, in: Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP), In Press

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Yang, K, Liu, Z., Xie, Q., Huang, J., Min, E. and Ananiadou, S., Selective Preference Optimization via Token-Level Reward Function Estimation, arXiv, 2024

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Yang, K, Liu, Z., Xie, Q., Huang, J., Zhang, T. and Ananiadou, S., MetaAligner: Towards Generalizable Multi-Objective Alignment of Language Models, in: Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS), 2024

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Yang, K, Zhang, T., Alhuzali, H. and Ananiadou, S., Cluster-Level Contrastive Learning for Emotion Recognition in Conversations (2023), in: IEEE Transactions on Affective Computing(1-12)

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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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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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Yang, K, Zhang, T. and Ananiadou, S., A Mental State Knowledge-Aware and Contrastive Network for Early Stress and Depression Detection on Social Media (2022), in: Information Processing and Management, 59:4(102961)

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Yang, K, Zhang, T., Kuang, Z., Xie, Q., Huang, J. and Ananiadou, S., MentaLLaMA: Interpretable Mental Health Analysis on Social Media with Large Language Models, in: Proceedings of WWW 2024, páginas 4489 - 4500, 2024

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