Ananiadou, S. - NaCTeM Publications

BROWSE
EXPORT
- Export all publications
- Export author
SORT BY
- Author
- Title
- Type/Journal
- Year
- Recently added
SITE
- Help
- About this site
GUEST USER
Guest
LOGIN
Name:

Password:

Deutsch, English, Nederlands, Norsk, Português, <more...>

Dear guest, welcome to this publication database. As an anonymous user, you will probably not have edit rights. Also, the collapse status of the topic tree will not be persistent. If you like to have these and other options enabled, you might ask Admin for a login account.

This site is powered by Aigaion - A PHP/Web based management system for shared and annotated bibliographies. For more information visit www.aigaion.de.

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

| 1-25 | 26-50 | 51-75 | 76-100 | 101-125 | 126-150 | 151-175 | 176-200 | 201-225 | 226-250 | 251-275 | 276-300 | 301-325 | 326-350 | 351-375 | 376-400 | 401-407 |

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), In Press

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

[DOI]
[URL]

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

[URL]

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

[DOI]
[URL]

Liu, Z., Zhang, X., Yang, K, Xie, Q., Huang, J. and Ananiadou, S., FMDLlama: Financial Misinformation Detection based on Large Language Models, arXiv, 2024

[URL]

Luo, Z., Liu, L., Ananiadou, S. and Xie, Q., Graph Contrastive Topic Model (2024), in: Expert Systems with Applications, 255:Part C(124631)

[DOI]
[URL]

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

[URL]

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

[DOI]
[URL]

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

[URL]

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

[DOI]
[URL]

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

[URL]

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

[URL]

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, arXiv, 2024

[URL]

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)

[DOI]
[URL]

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

[URL]

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

[URL]

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, pages 119- 126, 2024

[URL]

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

[URL]

Luo, Z., Xie, Q. and Ananiadou, S., The Lay Person’s Guide to Biomedicine: Orchestrating Large Language Models, arXiv, 2024

[URL]

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)

[DOI]
[URL]

Liu, Z., Liu, B, Thompson, P., Yang, K and 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

[DOI]
[URL]

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

[URL]

Ji, S., Zhang, T., Yang, K and Ananiadou, S., Rethinking large language models in mental health applications, arXiv, 2023

[URL]

Zhang, X., Xiang, R., Yuan, C., Feng, D., Han, W., Lopez-Lira, A., Liu, X. -Y., Ananiadou, S., Peng, M., Huang, J. and 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), pages 6236-6246, 2024

[DOI]
[URL]

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

[DOI]
[URL]

| 1-25 | 26-50 | 51-75 | 76-100 | 101-125 | 126-150 | 151-175 | 176-200 | 201-225 | 226-250 | 251-275 | 276-300 | 301-325 | 326-350 | 351-375 | 376-400 | 401-407 |

processing time: 0.0768 seconds.