Ananiadou, S. - NaCTeM Publications - Aigaion 2.0

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First name(s):	S.
Last name(s):	Ananiadou

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Yu, Z. and Ananiadou, S., How do Large Language Models Learn In-Context? Query and Key Matrices of In-Context Heads are Two Towers for Metric Learning, in: Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pages 3281–3292, 2024

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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, pages 3293–3306, 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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Hua, Y., Liu, F., Yang, K, Li, Z., Sheu, Y., Zhou, P., Moran, L. V., Ananiadou, S. and Beam, A., Large Language Models in Mental Health Care: a Scoping Review, arXiv, 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, pages 10777-10789, 2024

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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, pages 4489 - 4500, 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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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, pages 3267–3280, 2024

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Hu, G., Qin, K., Yuan, C., Peng, M., Lopez-Lira, A., Wang, B., Ananiadou, S., Huang, J. and Xie, Q., No Language is an Island: Unifying Chinese and English in Financial Large Language Models, Instruction Data, and Benchmarks, arXiv, 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, pages 468-477, 2024

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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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Zhang, T., Yang, K, Ji, S., Liu, B, Xie, Q. and Ananiadou, S., SuicidEmoji: Derived Emoji Dataset and Tasks for Suicide-Related Social Content, in: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '24), pages 1136 - 1141, 2024

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Thompson, P., Ananiadou, S., Basinas, I., Brinchmann, B. C., Cramer, C., Galea, K. S., Ge, C., Georgiadis, P., Kirkeleit, J., Kuijpers, E., Nguyen, N. T. H., Nuñez, R., Schlünssen, V., Stokholm, Z. A., Taher, E. A., Tinnerberg, H., van Tongeren, M. and Xie, Q., Supporting the working life exposome: Annotating occupational exposure for enhanced literature search (2024), in: PLoS ONE, 19:8(e0307844)

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Yuan, C., Xie, Q. and Ananiadou, S., Temporal relation extraction with contrastive prototypical sampling (2024), in: Knowledge-based Systems, 286(111410)

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

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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, pages 2917–2927, 2023

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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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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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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, pages 10846–10858, 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, pages 468–477, 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., CitationSum: Citation-aware Graph Contrastive Learning for Scientific Paper Summarization, in: Proceedings of the ACM Web Conference, pages 1843–1852, 2023

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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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