Yongli Mou

26 papers A* 1B 1C 1Journal 8Unranked 15
YearRankTypeTitle / Venue / Authors
2025 A* conf
LogicAD: Explainable Anomaly Detection via VLM-based Text Feature Extraction.
AAAI
Er Jin, Qihui Feng, Yongli Mou, Gerhard Lakemeyer, Stefan Decker, Oliver Simons, Johannes Stegmaier
2025 J jnl
LogicAD: Explainable Anomaly Detection via VLM-based Text Feature Extraction.
CoRR
Er Jin, Qihui Feng, Yongli Mou, Stefan Decker, Gerhard Lakemeyer, Oliver Simons, Johannes Stegmaier
2025 J jnl
On the Encapsulation of Medical Imaging AI Algorithms.
CoRR
Hans Meine, Yongli Mou, Guido P. M. Prause, Horst K. Hahn
2025 — conf
Semantic Annotation of Energy Data Using Ensemble Decision-Making with Large Language Models.
IJCKG
Zhiyu Pan, Yongli Mou, Fengshuo Hao, Yuting Gao, Stefan Decker, Antonello Monti
2025 J jnl
Unconsciously Forget: Mitigating Memorization; Without Knowing What is being Memorized.
CoRR
Er Jin, Yang Zhang, Yongli Mou, Yanfei Dong, Stefan Decker, Kenji Kawaguchi, Johannes Stegmaier
2025 — conf
WILLM: A System for Academic Writing Improvement Based on Large Language Models.
AIED (5)
Yongli Mou, Fatemeh Fathi, Ben Thillen, Stefan Decker
2024 J jnl
A novel model for the pavement distress segmentation based on multi-level attention DeepLabV3+.
Eng. Appl. Artif. Intell.
Feifei Li, Yongli Mou, Zeyu Zhang, Quan Liu, Sabina Jeschke
2024 J jnl
Improved Gradient Inversion Attacks and Defenses in Federated Learning.
IEEE Trans. Big Data
Jiahui Geng, Yongli Mou, Qing Li, Feifei Li, Oya Beyan, Stefan Decker, Chunming Rong
2024 — conf
Improving the Quality of Unstructured Cancer Data Using Large Language Models: A German Oncological Case Study.
MIE
Yongli Mou, Jonathan Lehmkuhl, Nicolas Sauerbrunn, Anja Köchel, Jens Panse, Daniel Truhn, Sulayman K. Sowe, Tim H. Brümmendorf, Stefan Decker
2024 — conf
Knowledge Graph-Enhanced Vision-to-Language Multimodal Models for Radiology Report Generation.
ESWC Satellite Events (2)
Yongli Mou
2024 — conf
Leveraging LLMs Few-shot Learning to Improve Instruction-driven Knowledge Graph Construction.
VLDB Workshops
Yongli Mou, Li Liu, Sulayman K. Sowe, Diego Collarana, Stefan Decker
2024 — conf
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.
LLMs4OL@ISWC
Yixin Peng, Yongli Mou, Bozhen Zhu, Sulayman K. Sowe, Stefan Decker
2024 — conf
RadLink: Linking Clinical Entities from Radiology Reports.
FLLM
Yongli Mou, Hanbin Chen, Gwendolyn Isabella Lode, Daniel Truhn, Sulayman K. Sowe, Stefan Decker
2024 — conf
The Design and Implementation of APLOS: An Automated PoLicy DOcument Summarisation System.
FLLM
Sulayman K. Sowe, Tobias Kiel, Alexander Tobias Neumann, Yongli Mou, Vassilios Peristeras, Stefan Decker
2024 — conf
Understanding Open Source Large Language Models: An Exploratory Study.
FLLM
Sulayman K. Sowe, Yongli Mou, Du Cheng, Lingxiao Kong, Alexander Tobias Neumann, Stefan Decker
2023 — conf
Distributed Privacy-Preserving Data Analysis in NFDI4Health With the Personal Health Train.
CoRDI
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
2023 J jnl
Privacy-Preserving Linkage of Distributed Datasets using the Personal Health Train.
CoRR
Maximilian Jugl, Sascha Welten, Yongli Mou, Yeliz Ucer Yediel, Oya Deniz Beyan, Ulrich Sax, Toralf Kirsten
2023 — conf
Self-sovereign Identity-based Access Control Management in Forestry 4.0.
FiCloud
Yongli Mou, Jiahang Chen, Zhenghao Zhang, Jürgen Roßmann, Stefan Decker
2023 B conf
Towards FAIR Data in Distributed Machine Learning Systems.
GLOBECOM
Yongli Mou, Fengyang Guo, Wei Lu, Yongzhao Li, Oya Beyan, Thomas Rose, Schahram Dustdar, Stefan Decker
2023 — conf
Towards Federated Machine Learning and Distributed Ledger Technology-based Data Monetization.
VLDB Workshops
Timo Himmelsbach, Yongli Mou, Stefan Decker, Armin Heinzl
2023 — conf
pFedV: Mitigating Feature Distribution Skewness via Personalized Federated Learning with Variational Distribution Constraints.
PAKDD (2)
Yongli Mou, Jiahui Geng, Feng Zhou, Oya Beyan, Chunming Rong, Stefan Decker
2022 C conf
Blockchain-based Cross-organizational Workflow Platform.
CloudCom
Jiahui Geng, Ali Akbar Rehman, Yongli Mou, Stefan Decker, Chunming Rong
2021 J jnl
Distributed Learning for Melanoma Classification using Personal Health Train.
CoRR
Yongli Mou, Sascha Welten, Yeliz Ucer Yediel, Toralf Kirsten, Oya Deniz Beyan
2021 — conf
Distributed Skin Lesion Analysis Across Decentralised Data Sources.
MIE
Yongli Mou, Sascha Welten, Mehrshad Jaberansary, Yeliz Ucer Yediel, Toralf Kirsten, Stefan Decker, Oya Beyan
2021 — conf
Optimized Federated Learning on Class-Biased Distributed Data Sources.
PKDD/ECML Workshops (1)
Yongli Mou, Jiahui Geng, Sascha Welten, Chunming Rong, Stefan Decker, Oya Beyan
2021 J jnl
Towards General Deep Leakage in Federated Learning.
CoRR
Jiahui Geng, Yongli Mou, Feifei Li, Qing Li, Oya Beyan, Stefan Decker, Chunming Rong