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@iMoonLab

iMoon: Intelligent Media and Cognition Group

README.md

🌙 iMoonLab

Intelligent Media and Cognition Group
清华大学 · 软件学院 · Tsinghua University, School of Software

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🧭 About Us

iMoonLab is a research group at Tsinghua University, School of Software. We study how intelligent systems can understand complex, unstructured media — from images, text, and 3D shapes to brain networks and knowledge — by modeling high-order relationships beyond pairwise connections.

Our research sits at the intersection of hypergraph computation, multimodal media understanding, and knowledge-driven AI. We build both foundational theory and open-source tools that turn research ideas into reusable code.

🧠 Hypergraph Learning🎯 Object & Scene Understanding🌐 Knowledge & LLMs🧬 Brain & Medical AI
High-order neural networks, structure learning, efficient inferenceDetection, 3D vision, multi-modal representationRAG, knowledge extraction, LLM reasoning on hypergraphsfMRI analysis, disease diagnosis, survival prediction

🔥 Featured

Hyper-Extract

Documents → structured knowledge. One command.

StarsPyPIDocs

uv tool install hyperextract
he parse paper.pdf -t general/academic_graph -o ./paper_kb/

🏗️ Core Libraries & Platforms

ProjectDescriptionStars
DeepHypergraphA PyTorch library for graph and hypergraph deep learning
THU-HyperGHypergraph learning toolbox and benchmarks
Hypergraph-DBHypergraph database with built-in visualization

🎯 Object Detection & 3D Vision

ProjectDescriptionVenueStars
yolov13YOLOv13: real-time detection with hypergraph-enhanced adaptive visual perceptionarXiv 2025
Hyper-YOLOWhen visual object detection meets hypergraph computationIEEE TPAMI 2025
MeshNetMesh neural network for 3D shape representationAAAI 2019
HGM2RHypergraph-based multi-modal representation for open-set 3D object retrievalIEEE TPAMI 2024
PVRNetPoint-view relation neural network for 3D shape recognitionAAAI 2019

🧠 Hypergraph Neural Networks

ProjectDescriptionVenueStars
HGNNHypergraph Neural Networks — foundational work on hypergraph convolutionAAAI 2019
DHGNNDynamic Hypergraph Neural Networks for dynamic structure learningIJCAI 2019
LightHGNNDistilling hypergraph neural networks into MLPs for 100× faster inferenceICLR 2024
KHGNNKernel Hypergraph Neural NetworksIEEE TPAMI 2025
SS-HTSelf-supervised hypergraph training via structure-aware learningIEEE TPAMI 2025
HGNN-ShieldDefending hypergraph neural networks against high-order structure attackIEEE TPAMI

🌐 Knowledge, RAG & LLMs

ProjectDescriptionVenueStars
Hyper-RAGCombating LLM hallucinations with hypergraph-driven retrieval-augmented generationNature Communications 2026
LLM4HypergraphCan large language models comprehend hypergraphs beyond graphs?ICLR 2025
HICHypergraph Isomorphism ComputationIEEE TPAMI 2024

🧬 Brain Networks & Medical AI

ProjectDescriptionVenueStars
DHGFormerDynamic hierarchical graph transformer for disorder brain disease diagnosisMICCAI 2025
LHDFormerAdaptive embedding for long-range high-order dependencies on fMRIMICCAI 2025
DIBrainExploring dynamic interpretable brain networks via hierarchical graph transformerPR 2026
HGSTHypergraph-based semantic and topological self-supervised learning for brain disease diagnosis2025
PAGHCMultimodal hypergraph guide learning for non-invasive ccRCC survival prediction2025

📬 Connect

Intelligent Media · Structured Knowledge · Cognition

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  1. HGNNHGNNPublic

    Hypergraph Neural Networks (AAAI 2019)

    Python 847 159

  2. DeepHypergraphDeepHypergraphPublic

    A pytorch library for graph and hypergraph computation.

    Python 876 89

  3. Hyper-YOLOHyper-YOLOPublic

    The source code of IEEE TPAMI 2025 "Hyper-YOLO: When Visual Object Detection Meets Hypergraph Computation".

    Python 230 19

  4. Hyper-RAGHyper-RAGPublic

    "Hyper-RAG: Combating LLM Hallucinations using Hypergraph-Driven Retrieval-Augmented Generation" by Yifan Feng, Hao Hu, Shihui Ying, Xingliang Hou, Shiquan Liu, Mingyuan Yang, Junchang Li, Shaoyi D…

    Python 311 53

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