Ananiadou, S. - NaCTeM Publications

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

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

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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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Yu, Z., Belinkov, Y. and Ananiadou, S., Back Attention: Understanding and Enhancing Multi-Hop Reasoning in Large Language Models, in: Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP), páginas 11257–11272, 2025

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Kabir, M., Abrar, A. and Ananiadou, S., Break the Checkbox: Challenging Closed-Style Evaluations of Cultural Alignment in LLMs, in: Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP), páginas 24–51, 2025

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Yu, Z. and Ananiadou, S., Understanding and Mitigating Gender Bias in LLMs via Interpretable Neuron Editing, arXiv, 2025

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Abrar, A., Tabassum Oeshy, N., Kabir, M. and Ananiadou, S., Religious Bias Landscape in Language and Text-to-Image Models: Analysis, Detection, and Debiasing Strategies (2025), in: AI & SOCIETY

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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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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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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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Yano, K., Luo, Z., Huang, J., Xie, Q., Asada, M., Yuan, C., Yang, K, Miwa, M., Ananiadou, S. and Tsujii, J., ELAINE-medLLM: Lightweight English Japanese Chinese Trilingual Large Language Model for Bio-medical Domain, in: Proceedings of the 31st International Conference on Computational Linguistics (COLING 2025), páginas 4670–4688, 2025

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Yu, Z. and Ananiadou, S., Interpreting Arithmetic Mechanism in Large Language Models through Comparative Neuron Analysis, in: Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, páginas 3293–3306, 2024

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Yu, Z. and Ananiadou, S., Understanding Multimodal LLMs: the Mechanistic Interpretability of Llava in Visual Question Answering, arXiv, 2024

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Yu, Z. and Ananiadou, S., Neuron-Level Knowledge Attribution in Large Language Models, in: Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, páginas 3267–3280, 2024

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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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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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Yano, K., Miwa, M. and Ananiadou, S., IRIS: Iterative Improvement of Distantly Supervised Named Entity Annotations, Research Square, 2024

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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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Goldsack, T., Luo, Z., Xie, Q., Scarton, C., Shardlow, M., Ananiadou, S. and Lin, C., Overview of the BioLaySumm 2023 Shared Task on Lay Summarization of Biomedical Research Articles, in: Proceedings of the 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks, páginas 468-477, 2024

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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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Luo, Z., Yuan, C., Xie, Q. and 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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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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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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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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