Yongli Mou

According to our database, Yongli Mou authored at least 18 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

LogicAD: Explainable Anomaly Detection via VLM-based Text Feature Extraction.

Er Jin, Qihui Feng, Yongli Mou, Stefan Decker, Gerhard Lakemeyer, Oliver Simons, Johannes Stegmaier

CoRR, January, 2025

2024

Improved Gradient Inversion Attacks and Defenses in Federated Learning.

Jiahui Geng, Yongli Mou, Qing Li, Feifei Li, Oya Beyan, Stefan Decker, Chunming Rong

IEEE Trans. Big Data, December, 2024

A novel model for the pavement distress segmentation based on multi-level attention DeepLabV3+.

Feifei Li, Yongli Mou, Zeyu Zhang, Quan Liu, Sabina Jeschke

Eng. Appl. Artif. Intell., 2024

Leveraging LLMs Few-shot Learning to Improve Instruction-driven Knowledge Graph Construction.

Yongli Mou, Li Liu, Sulayman K. Sowe, Diego Collarana, Stefan Decker

Proceedings of Workshops at the 50th International Conference on Very Large Data Bases, 2024

Improving the Quality of Unstructured Cancer Data Using Large Language Models: A German Oncological Case Study.

Yongli Mou, Jonathan Lehmkuhl, Nicolas Sauerbrunn, Anja Köchel, Jens Panse, Daniel Truh, Sulayman K. Sowe, Tim H. Brümmendorf, Stefan Decker

Proceedings of the Digital Health and Informatics Innovations for Sustainable Health Care Systems, 2024

RWTH-DBIS at LLMs4OL 2024 Tasks A and B Knowledge-Enhanced Domain-Specific Continual Learning and Prompt-Tuning of Large Language Models for Ontology Learning.

Yixin Peng, Yongli Mou, Bozhen Zhu, Sulayman K. Sowe, Stefan Decker

Proceedings of the LLMs4OL 2024: The 1st Large Language Models for Ontology Learning Challenge at the 23rd ISWC, 2024

Knowledge Graph-Enhanced Vision-to-Language Multimodal Models for Radiology Report Generation.

Yongli Mou

Proceedings of the Semantic Web: ESWC 2024 Satellite Events, 2024

2023

Privacy-Preserving Linkage of Distributed Datasets using the Personal Health Train.

Maximilian Jugl, Sascha Welten, Yongli Mou, Yeliz Ucer Yediel, Oya Deniz Beyan, Ulrich Sax, Toralf Kirsten

CoRR, 2023

Towards Federated Machine Learning and Distributed Ledger Technology-based Data Monetization.

Timo Himmelsbach, Yongli Mou, Stefan Decker, Armin Heinzl

Proceedings of the Joint Proceedings of Workshops at the 49th International Conference on Very Large Data Bases (VLDB 2023), Vancouver, Canada, August 28, 2023

pFedV: Mitigating Feature Distribution Skewness via Personalized Federated Learning with Variational Distribution Constraints.

Yongli Mou, Jiahui Geng, Feng Zhou, Oya Beyan, Chunming Rong, Stefan Decker

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023

Towards FAIR Data in Distributed Machine Learning Systems.

Yongli Mou, Fengyang Guo, Wei Lu, Yongzhao Li, Oya Beyan, Thomas Rose, Schahram Dustdar, Stefan Decker

Proceedings of the IEEE Global Communications Conference, 2023

Self-sovereign Identity-based Access Control Management in Forestry 4.0.

Yongli Mou, Jiahang Chen, Zhenghao Zhang, Jürgen Roßmann, Stefan Decker

Proceedings of the 10th International Conference on Future Internet of Things and Cloud, 2023

Distributed Privacy-Preserving Data Analysis in NFDI4Health With the Personal Health Train.

Yongli Mou, Feifei Li, Sven Weber, Sabith Haneef, Hans Meine, Liliana Caldeira, Mehrshad Jaberansary, Sascha Welten, Yeliz Ucer Yediel, Guido P. M. Prause, Stefan Decker, Oya Beyan, Toralf Kirsten

Proceedings of the 1st Conference on Research Data Infrastructure - Connecting Communities, 2023

2022

Blockchain-based Cross-organizational Workflow Platform.

Jiahui Geng, Ali Akbar Rehman, Yongli Mou, Stefan Decker, Chunming Rong

Proceedings of the IEEE International Conference on Cloud Computing Technology and Science, 2022

2021

Towards General Deep Leakage in Federated Learning.

Jiahui Geng, Yongli Mou, Feifei Li, Qing Li, Oya Beyan, Stefan Decker, Chunming Rong

CoRR, 2021

Distributed Learning for Melanoma Classification using Personal Health Train.

Yongli Mou, Sascha Welten, Yeliz Ucer Yediel, Toralf Kirsten, Oya Deniz Beyan

CoRR, 2021

Optimized Federated Learning on Class-Biased Distributed Data Sources.

Yongli Mou, Jiahui Geng, Sascha Welten, Chunming Rong, Stefan Decker, Oya Beyan

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2021

Distributed Skin Lesion Analysis Across Decentralised Data Sources.

Yongli Mou, Sascha Welten, Mehrshad Jaberansary, Yeliz Ucer Yediel, Toralf Kirsten, Stefan Decker, Oya Beyan

Proceedings of the Public Health and Informatics, 2021