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Yushun Dong

Florida State University · US
Area of research
Artificial Intelligence · Materials Chemistry
Research interest
Research topics from publications: Few-Shot Graph Out-of-Distribution Detection with LLMs; KG-CF: Knowledge Graph Completion with Context Filtering under the Guidance of Large Language Models. Representative work: Large Language Models (LLMs) have shown impressive performance in various tasks, including knowledge graph completion (KGC). However, current studies mostly apply LLMs to classification tasks, like identifying missing triplets, rather than ranking-based tasks, where the model ranks candidate entities based on plausibility. This focus limits the practical use of LLMs in KGC, as real-world applications prioritize highly plausible triplets. Additionally, while graph paths can help infer the existence of missing triplets and improve completion accuracy, they often contain redundant information. To address these issues, we propose KG-CF, a framework tailored for ranking-based KGC tasks. KG-CF lev
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Recent publications

Few-Shot Graph Out-of-Distribution Detection with LLMs
Lecture notes in computer science 2025cited by 1position: middledoi
KG-CF: Knowledge Graph Completion with Context Filtering under the Guidance of Large Language Models
2024cited by 1position: middledoi

Grants

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Frequent collaborators

Yue Zhao · North Carolina State University1 papers (2025–2025)Ryan A. Rossi · University of Maryland, College Park1 papers (2025–2025)Jundong Li · Guangdong Polytechnic Normal University1 papers (2024–2024)Haochen Liu · University of Virginia1 papers (2024–2024)Qi Wang · Fudan University1 papers (2024–2024)Zaiyi Zheng · University of Virginia1 papers (2024–2024)Song Wang · University of Virginia1 papers (2024–2024)Mengyuan Li · London Cancer1 papers (2025–2025)Ziyi Wang · Wenzhou Medical University1 papers (2025–2025)Haoyan Xu · University of Southern California1 papers (2025–2025)