Ananiadou, S.
Vorname(n): S.
Nachname(n): Ananiadou

Publikationen von Ananiadou, S. sortiert nach Zeitschrift und Typ
| 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 | 401-425 | 426-442 |


Publikationen vom Typ Inproceedings


2025

Yang, K, Liu, Z., Xie, Q., Huang, J., Min, E. und 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), Seiten 7032–7056, 2025
[DOI]
[URL]
Zhang, X., Wei, Q., Zhu, Y., Zhang, L., Zhou, D. und 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, Seiten 16338–16356, 2025
[DOI]
[URL]
Zhang, X., Wei, Q., Zhu, Y., Wu, F. und Ananiadou, S., THCM-CAL: Temporal-Hierarchical Causal Modelling with Conformal Calibration for Clinical Risk Prediction, in: Findings of the Association for Computational Linguistics: EMNLP 2024, Seiten 916–928, 2025
[DOI]
[URL]
Partalidou, E., Passali, T., Zerva, C., Tsoumakas, G. und Ananiadou, S., Towards Trustworthy Summarization of Cardiovascular Articles: A Factuality-and-Uncertainty-Aware Biomedical LLM Approach, in: Proceedings of the 2nd Workshop on Uncertainty-Aware NLP (UncertaiNLP 2025), Seiten 200–207, 2025
[DOI]
[URL]

2024

Yuan, C., Xie, Q., Huang, J. und 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), Seiten 1963 - 1974, 2024
[URL]
Liu, Z., Liu, B, Thompson, P., Yang, K und 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), Seiten 4649 - 4656, 2024
[DOI]
[URL]
Zhang, X., Xiang, R., Yuan, C., Feng, D., Han, W., Lopez-Lira, A., Liu, X. -Y., Ananiadou, S., Peng, M., Huang, J. und 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), Seiten 6236-6246, 2024
[DOI]
[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. und 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, Seiten 119- 126, 2024
[URL]
Wang, Y., Feng, D., Dai, Y., Chen, Z., Huang, J., Ananiadou, S., Xie, Q. und 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]
Yu, Z. und 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, Seiten 3281–3292, 2024
[DOI]
[URL]
Yu, Z. und 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, Seiten 3293–3306, 2024
[DOI]
[URL]
Yang, K, Liu, Z., Xie, Q., Huang, J., Zhang, T. und 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]
Yu, Z. und Ananiadou, S., Neuron-Level Knowledge Attribution in Large Language Models, in: Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, Seiten 3267–3280, 2024
[DOI]
[URL]
Goldsack, T., Luo, Z., Xie, Q., Scarton, C., Shardlow, M., Ananiadou, S. und 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, Seiten 468-477, 2024
[DOI]
[URL]
Zhang, T., Yang, K, Ji, S., Liu, B, Xie, Q. und 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), Seiten 1136 - 1141, 2024
[URL]

2023

Liu, B, Schlegel, V., Batista-Navarro, R. und Ananiadou, S., Argument mining as a multi-hop generative machine reading comprehension task, in: Findings of the Association for Computational Linguistics: EMNLP 2023, Seiten 10846–10858, 2023
[URL]
Luo, Z., Xie, Q. und Ananiadou, S., CitationSum: Citation-aware Graph Contrastive Learning for Scientific Paper Summarization, in: Proceedings of the ACM Web Conference, Seiten 1843–1852, 2023
[DOI]
[URL]
Miwa, M. und Ananiadou, S., DISTANT: Distantly Supervised Entity Span Detection and Classification, in: Proceedings of BioNLP 2023, Seiten 171–177, 2023
[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 | 401-425 | 426-442 |