1 citations · 1 across the 2 of their papers we have counts for
5 papers
Cog-RAG: Cognitive-Inspired Dual-Hypergraph with Theme Alignment Retrieval-Augmented Generation
Hao Hu, Yifan Feng, Ruoxue Li +5
Retrieval-Augmented Generation (RAG) enhances the response quality and domain-specific performance of large language models (LLMs) by incorporating external knowledge to combat hal…
YOLOv13: Real-Time Object Detection with Hypergraph-Enhanced Adaptive Visual Perception
Mengqi Lei, Siqi Li, Yihong Wu +7
The YOLO series models reign supreme in real-time object detection due to their superior accuracy and computational efficiency. However, both the convolutional architectures of YOL…
SoftHGNN: Soft Hypergraph Neural Networks for General Visual Recognition
Mengqi Lei, Yihong Wu, Siqi Li +4
Visual recognition relies on understanding the semantics of image tokens and their complex interactions. Mainstream self-attention methods, while effective at modeling global pair-…
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…
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…