6 papers
Hyper-KGGen: A Skill-Driven Knowledge Extractor for High-Quality Knowledge Hypergraph Generation
Rizhuo Huang, Yifan Feng, Rundong Xue +5
Knowledge hypergraphs surpass traditional binary knowledge graphs by encapsulating complex n-ary atomic facts, providing a more comprehensive paradigm for semantic representation.…
Hypergraph Foundation Model
Yue Gao, Yifan Feng, Shiquan Liu +4
Hypergraph neural networks (HGNNs) effectively model complex high-order relationships in domains like protein interactions and social networks by connecting multiple vertices throu…
Hyper-RAG: Combating LLM Hallucinations using Hypergraph-Driven Retrieval-Augmented Generation
Yifan Feng, Hao Hu, Xingliang Hou +5
Large language models (LLMs) have transformed various sectors, including education, finance, and medicine, by enhancing content generation and decision-making processes. However, t…
Beyond Graphs: Can Large Language Models Comprehend Hypergraphs?
Yifan Feng, Chengwu Yang, Xingliang Hou +4
Existing benchmarks like NLGraph and GraphQA evaluate LLMs on graphs by focusing mainly on pairwise relationships, overlooking the high-order correlations found in real-world data.…
Hyper-YOLO: When Visual Object Detection Meets Hypergraph Computation
Yifan Feng, Jiangang Huang, Shaoyi Du +6
We introduce Hyper-YOLO, a new object detection method that integrates hypergraph computations to capture the complex high-order correlations among visual features. Traditional YOL…
LightHGNN: Distilling Hypergraph Neural Networks into MLPs for Faster Inference
Yifan Feng, Yihe Luo, Shihui Ying +1
Hypergraph Neural Networks (HGNNs) have recently attracted much attention and exhibited satisfactory performance due to their superiority in high-order correlation modeling. Howeve…