zjukg / MoMoK

[Paper][Preprint 2024] Mixture of Modality Knowledge Experts for Robust Multi-modal Knowledge Graph Completion

https://arxiv.org/abs/2405.16869

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contrastive-learning knowledge-graph knowledge-graph-completion knowledge-graph-embeddings mixture-of-experts multi-modal-fusion multi-modal-knowledge-graph mutual-information

readme

Mixture of Modality Knowledge Experts for Robust Multi-modal Knowledge Graph Completion

🌈 Overview

model

🔬 Dependencies

Python==3.9
numpy==1.24.2
scikit_learn==1.2.2
torch==2.0.0
tqdm==4.64.1

💻 Data preparation

The multi-model embedding of MMKGs are too large so you should download them from the Google Drive Link (updated soon).

📕 Train and Evaluation

You can refer to the training scripts in scripts/train.sh to reproduce our experiment results. Here is an example for DB15K dataset.

nohup python train.py --cuda 0 --lr 0.001 --mu 0.0001 --dim 200 --dataset MKG-W --epochs 2000 > log.txt &

nohup python train.py --cuda 1 --lr 0.0005 --mu 0.0001 --dim 300 --dataset MKG-Y --epochs 2000 > log.txt &

The evaluation results will be printed in the command line after training.

🤝 Cite:

@misc{zhang2024mixture,
      title={Mixture of Modality Knowledge Experts for Robust Multi-modal Knowledge Graph Completion}, 
      author={Yichi Zhang and Zhuo Chen and Lingbing Guo and Yajing Xu and Binbin Hu and Ziqi Liu and Wen Zhang and Huajun Chen},
      year={2024},
      eprint={2405.16869},
      archivePrefix={arXiv},
      primaryClass={cs.AI}
}