Repo for studying about multi-modal learning which focus on multi-modal knowlegde graphs and its applications

• 1. Surveys
  • 2024
  • 2023
  • 2022
• 2. Applications
  • 2.1 In-MMKG Applications
  • 2.2 Out-of-MMKG Applications
  • 2.3 Domain Applications

2024

1. Wang, S., Zhu, Y., Liu, H., Zheng, Z., Chen, C., & Li, J. (2024). Knowledge editing for large language models: A survey. ACM Computing Surveys, 57(3), 1-37.

2. Pan, S., Luo, L., Wang, Y., Chen, C., Wang, J., & Wu, X. (2024). Unifying large language models and knowledge graphs: A roadmap. IEEE Transactions on Knowledge and Data Engineering, 36(7), 3580-3599.

3. Liang, P. P., Zadeh, A., & Morency, L. P. (2024). Foundations & trends in multimodal machine learning: Principles, challenges, and open questions. ACM Computing Surveys, 56(10), 1-42.

4. Liang, K., Meng, L., Liu, M., Liu, Y., Tu, W., Wang, S., ... & He, K. (2024). A survey of knowledge graph reasoning on graph types: Static, dynamic, and multi-modal. IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(12), 9456-9478.

5. Chen, Z., Zhang, Y., Fang, Y., Geng, Y., Guo, L., Chen, X., ... & Chen, H. (2024). Knowledge graphs meet multi-modal learning: A comprehensive survey. arXiv preprint arXiv:2402.05391.

6. Liang, W., Meo, P. D., Tang, Y., & Zhu, J. (2024). A survey of multi-modal knowledge graphs: Technologies and trends. ACM Computing Surveys, 56(11), 1-41.

7. Panchendrarajan, R., & Zubiaga, A. (2024). Synergizing machine learning & symbolic methods: A survey on hybrid approaches to natural language processing. Expert Systems with Applications, 251, 124097.

2023

1. Zhong, L., Wu, J., Li, Q., Peng, H., & Wu, X. (2023). A comprehensive survey on automatic knowledge graph construction. ACM Computing Surveys, 56(4), 1-62.

2. Chen, Y., Ge, X., Yang, S., Hu, L., Li, J., & Zhang, J. (2023). A survey on multimodal knowledge graphs: Construction, completion and applications. Mathematics, 11(8), 1815.

2022

1. Zhu, X., Li, Z., Wang, X., Jiang, X., Sun, P., Wang, X., ... & Yuan, N. J. (2022). Multi-modal knowledge graph construction and application: A survey. IEEE Transactions on Knowledge and Data Engineering, 36(2), 715-735.

1. Chen, X., Zhang, N., Li, L., Deng, S., Tan, C., Xu, C., Huang, F., Si, L., & Chen, H. (2022). Hybrid transformer with multi-level fusion for multimodal knowledge graph completion. arXiv. https://arxiv.org/abs/2205.02357

2. Wilcke, W., Bloem, P., de Boer, V., van ’t Veer, R., & van Harmelen, F. (2020). End-to-end entity classification on multimodal knowledge graphs. arXiv. https://arxiv.org/abs/2003.12383

1. Mogadala, A., Bista, U., Xie, L., & Rettinger, A. (2017). Describing natural images containing novel objects with knowledge guided assistance. arXiv. https://arxiv.org/abs/1710.06303

2. Wang, P., Wu, Q., Shen, C., van den Hengel, A., & Dick, A. (2015). Explicit knowledge-based reasoning for visual question answering. arXiv. https://arxiv.org/abs/1511.02570

3. Hou, J., Wu, X., Qi, Y., Zhao, W., Luo, J., & Jia, Y. (2019). Relational reasoning using prior knowledge for visual captioning. arXiv. https://arxiv.org/abs/1906.01290

4. Zhao, W., Hu, Y., Wang, H., Wu, X., & Luo, J. (2021). Boosting entity-aware image captioning with multi-modal knowledge graph. arXiv. https://arxiv.org/abs/2107.11970