Ananiadou, S. - NaCTeM Publications - Aigaion 2.0

ANSICHT
EXPORT
- Alle Publikationen exportieren
- Autor exportieren
SORTIERE NACH
- Autor
- Titel
- Typ/Zeitschrift
- Jahr
- Erstelldatum
SYSTEM
- Hilfe
- Über diese Seite
GASTNUTZER
Guest
ANMELDUNG
Name:

Passwort:

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

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.

Vorname(n):	S.
Nachname(n):	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 | 376-389 |

Liu, Z., Liu, B, Thompson, P., Yang, K, Jain, R. und Ananiadou, S., ConspEmoLLM: Conspiracy Theory Detection Using an Emotion-Based Large Language Model, arXiv, 2024

[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, arXiv, 2024

[URL]

Liu, Z., Yang, K, Zhang, T., Xie, Q., Yu, Z. und Ananiadou, S., EmoLLMs: A Series of Emotional Large Language Models and Annotation Tools for Comprehensive Affective Analysis, arXiv, 2024

[URL]

Liu, Z., Zhang, T., Yang, K, Thompson, P., Yu, Z. und Ananiadou, S., Emotion detection for misinformation: A review (2024), in: Information Fusion, 107(102300)

[DOI]

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, arXiv, 2024

[URL]

Hua, Y., Liu, F., Yang, K, Li, Z., Sheu, Y., Zhou, P., Moran, L. V., Ananiadou, S. und Beam, A., Large Language Models in Mental Health Care: a Scoping Review, arXiv, 2024

[URL]

Bishop, J., Xie, Q. und Ananiadou, S., LongDocFACTScore: Evaluating the Factuality of Long Document Abstractive Summarisation, in: Proceedings of LREC-COLING 2024, Seiten 10777-10789, 2024

[URL]

Yang, K, Zhang, T., Kuang, Z., Xie, Q., Huang, J. und Ananiadou, S., MentaLLaMA: Interpretable Mental Health Analysis on Social Media with Large Language Models, in: Proceedings of WWW 2024, Seiten 4489 - 4500, 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]

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

[DOI]
[URL]

Yang, K, Zhang, T. und Ananiadou, S., A Bipartite Graph is All We Need for Enhancing Emotional Reasoning with Commonsense Knowledge, in: Proceedings of CIKM 2023, Seiten 2917–2927, 2023

[URL]

Cao, J., van Veen, E. M., Peek, N., Renehan, A. G und 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)

[DOI]

Xie, Q., Luo, Z. und Ananiadou, S., A Survey for Biomedical Text Summarization: From Pre-trained to Large Language Models, arXiv, 2023

[URL]

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]

Dwivedi, Y. K., Hughes, L., Bhadeshia, H. K. D. H., Ananiadou, S., Cohn, A. G., Cole, J. M., Conduit, G. J., Desarkar, M. S. und Wang, X., Artificial intelligence (AI) futures: India-UK collaborations emerging from the 4th Royal Society Yusuf Hamied workshop (2023), in: International Journal of Information Management(102725)

[DOI]
[URL]

Yuan, C., Xie, Q., Huang, J. und Ananiadou, S., Back to the Future: Towards Explainable Temporal Reasoning with Large Language Models, arXiv, 2023

[URL]

Goldsack, T., Luo, Z., Xie, Q., Scarton, C., Shardlow, M., Ananiadou, S. und Lin, C., BioLaySumm 2023 Shared Task: Lay Summarisation of Biomedical Research Articles, in: Proceedings of BioNLP 2023, Seiten 468–477, 2023

[URL]

Luo, Z., Xie, Q. und Ananiadou, S., ChatGPT as a Factual Inconsistency Evaluator for Text Summarization, arXiv, 2023

[DOI]

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]

Yang, K, Zhang, T., Alhuzali, H. und Ananiadou, S., Cluster-Level Contrastive Learning for Emotion Recognition in Conversations (2023), in: IEEE Transactions on Affective Computing(1-12)

[DOI]
[URL]

Vasilakes, J., Georgiadis, P., Nguyen, N. T. H., Miwa, M. und Ananiadou, S., Contextualized Medication Event Extraction with Levitated Markers (2023), in: Journal of Biomedical Informatics(104347)

[DOI]
[URL]

Yang, K, Zhang, T. und Ananiadou, S., Disentangled Variational Autoencoder for Emotion Recognition in Conversations (2023), in: IEEE Transactions on Affective Computing(1-12)

[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]

Ji, S., Zhang, T., Yang, K und Ananiadou, S., Domain-specific Continued Pretraining of Language Models for Capturing Long Context in Mental Health, arXiv, 2023

[URL]

Zhang, T., Yang, K, Shaoxiong, J. und Ananiadou, S., Emotion fusion for mental illness detection from social media: A survey (2023), in: Information Fusion, 92(231-246)

[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 | 376-389 |

Ausführdauer: 0.0876 Sekunden.