Distributed Skin Lesion Analysis Across Decentralised Data Sources. - Yongli Mou; Sascha Welten; Mehrshad Jaberansary; Yeliz Ucer Yediel; Toralf Kirsten; Stefan Decker; Oya Beyan (MIE, 2021)

Optimized Federated Learning on Class-Biased Distributed Data Sources. - Yongli Mou; Jiahui Geng; Sascha Welten; Chunming Rong; Stefan Decker; Oya Beyan (PKDD/ECML Workshops (1), 2021)

Distributed Learning for Melanoma Classification using Personal Health Train. - Yongli Mou; Sascha Welten; Yeliz Ucer Yediel; Toralf Kirsten; Oya Deniz Beyan (CoRR, 2021)

Towards General Deep Leakage in Federated Learning. - Jiahui Geng; Yongli Mou; Feifei Li; Qing Li 038; Oya Beyan; Stefan Decker; Chunming Rong (CoRR, 2021)

Blockchain-based Cross-organizational Workflow Platform. - Jiahui Geng; Ali Akbar Rehman; Yongli Mou; Stefan Decker; Chunming Rong (CloudCom, 2022)

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; et al. (CoRDI, 2023)

Self-sovereign Identity-based Access Control Management in Forestry 4.0. - Yongli Mou; Jiahang Chen; Zhenghao Zhang; Jürgen Roßmann; Stefan Decker (FiCloud, 2023)

Towards FAIR Data in Distributed Machine Learning Systems. - Yongli Mou; Fengyang Guo; Wei Lu; Yongzhao Li; Oya Beyan; Thomas Rose 001; Schahram Dustdar; Stefan Decker (GLOBECOM, 2023)

pFedV: Mitigating Feature Distribution Skewness via Personalized Federated Learning with Variational Distribution Constraints. - Yongli Mou; Jiahui Geng; Feng Zhou 011; Oya Beyan; Chunming Rong; Stefan Decker (PAKDD (2), 2023)

Towards Federated Machine Learning and Distributed Ledger Technology-based Data Monetization. - Timo Himmelsbach; Yongli Mou; Stefan Decker; Armin Heinzl (VLDB Workshops, 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)

Knowledge Graph-Enhanced Vision-to-Language Multimodal Models for Radiology Report Generation. - Yongli Mou (ESWC Satellite Events (2), 2024)

RadLink: Linking Clinical Entities from Radiology Reports. - Yongli Mou; Hanbin Chen; Gwendolyn Isabella Lode; Daniel Truhn; Sulayman K. Sowe; Stefan Decker (FLLM, 2024)

The Design and Implementation of APLOS: An Automated PoLicy DOcument Summarisation System. - Sulayman K. Sowe; Tobias Kiel; Alexander Tobias Neumann; Yongli Mou; Vassilios Peristeras; Stefan Decker (FLLM, 2024)

Understanding Open Source Large Language Models: An Exploratory Study. - Sulayman K. Sowe; Yongli Mou; Du Cheng; Lingxiao Kong; Alexander Tobias Neumann; Stefan Decker (FLLM, 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 (LLMs4OL@ISWC, 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 Truhn; Sulayman K. Sowe; Tim H. Brümmendorf; Stefan Decker (MIE, 2024)

Leveraging LLMs Few-shot Learning to Improve Instruction-driven Knowledge Graph Construction. - Yongli Mou; Li Liu; Sulayman K. Sowe; Diego Collarana; Stefan Decker (VLDB Workshops, 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)

Improved Gradient Inversion Attacks and Defenses in Federated Learning. - Jiahui Geng; Yongli Mou; Qing Li 038; Feifei Li; Oya Beyan; Stefan Decker; Chunming Rong (IEEE Trans. Big Data, 2024)

LogicAD: Explainable Anomaly Detection via VLM-based Text Feature Extraction. - Er Jin; Qihui Feng; Yongli Mou; Gerhard Lakemeyer; Stefan Decker; Oliver Simons; Johannes Stegmaier (AAAI, 2025)

WILLM: A System for Academic Writing Improvement Based on Large Language Models. - Yongli Mou; Fatemeh Fathi; Ben Thillen; Stefan Decker (AIED (5), 2025)

On the Encapsulation of Medical Imaging AI Algorithms. - Hans Meine; Yongli Mou; Guido P. M. Prause; Horst K. Hahn (CoRR, 2025)