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Luo, Z., Yuan, C., Xie, Q. en 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, In Press

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. en 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, In Press

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

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Zhang, X., Wei, Q., Zhu, Y., Zhang, L., Zhou, D. en Ananiadou, S., SynGraph: A Dynamic Graph-LLM Synthesis Framework for Sparse Streaming User Sentiment Modeling, in: Findings of the Association for Computational Linguistics: ACL 2025, In Press

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Yu, Z., Belinkov, Y. en Ananiadou, S., Back Attention: Understanding and Enhancing Multi-Hop Reasoning in Large Language Models, arXiv, 2025

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Kabir, M., Abrar, A. en Ananiadou, S., Break the Checkbox: Challenging Closed-Style Evaluations of Cultural Alignment in LLMs, arXiv, 2025

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Liu, Z., Thompson, P., Rong, J. en Ananiadou, S., ConspEmoLLM-v2: A robust and stable model to detect sentiment-transformed conspiracy theories, arXiv, 2025

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

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Yano, K., Luo, Z., Huang, J., Xie, Q., Asada, M., Yuan, C., Yang, K, Miwa, M., Ananiadou, S. en 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), pagina's 4670–4688, 2025

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Cao, Y., Li, H., Yu, Y., Reddy Javaji, S., He, Y., Huang, J., Zhu, Z., Xie, Q., Liu, X. -Y., Subbalakshmi, K., Qiu, M., Ananiadou, S. en Nie., J. -Y., FinAudio: A Benchmark for Audio Large Language Models in Financial Applications, 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. en 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), pagina's 271–276, 2025

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Kabir, M., Tahsin, T. en Ananiadou, S., From n-gram to Attention: How Model Architectures Learn and Propagate Bias in Language Modelin, arXiv, 2025

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Yu, Z. en Ananiadou, S., Locate-then-Merge: Neuron-Level Parameter Fusion for Mitigating Catastrophic Forgetting in Multimodal LLMs, arXiv, 2025

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

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Peng, X., Papadopoulos, T., Soufleri, E., Giannouris, P., Xiang, R., Wang, Y., Qian, L., Huang, J., Xie, Q. en Ananiadou, S., Plutus: Benchmarking Large Language Models in Low-Resource Greek Finance, arXiv, 2025

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Abrar, A., Tabassum Oeshy, N., Kabir, M. en Ananiadou, S., Religious Bias Landscape in Language and Text-to-Image Models: Analysis, Detection, and Debiasing Strategies, arXiv, 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. en Xie, Q., Retrieval-augmented Large Language Models for Financial Time Series Forecasting, arXiv, 2025

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Liu, Z., Yang, K, Hovy, E. en 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. en Ananiadou, S., Subjective Logic Encodings, arXiv, 2025

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

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Luo, Z., Yuan, C., Xie, Q. en 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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Dwivedi, Y. K., Hughes, L., Bhadeshia, H. K. D. H., Ananiadou, S., Cohn, A. G., Cole, J. M., Conduit, G. J., Desarkar, M. S. en 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. en 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), pagina's 1963 - 1974, 2024

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Liu, Z., Liu, B, Thompson, P., Yang, K en 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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Zhang, X., Xiang, R., Yuan, C., Feng, D., Han, W., Lopez-Lira, A., Liu, X. -Y., Ananiadou, S., Peng, M., Huang, J. en Xie, Q., Dólares or Dollars? Unraveling the Bilingual Prowess of Financial LLMs Between Spanish and English, in: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '24), pagina's 6236-6246, 2024

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