Summary of Multi-domain Knowledge Graph Collaborative Pre-training and Prompt Tuning For Diverse Downstream Tasks, by Yichi Zhang et al.
Multi-domain Knowledge Graph Collaborative Pre-training and Prompt Tuning for Diverse Downstream Tasks
by Yichi Zhang, Binbin Hu, Zhuo Chen, Lingbing Guo, Ziqi Liu, Zhiqiang Zhang, Lei Liang, Huajun Chen, Wen Zhang
First submitted to arxiv on: 21 May 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel knowledge graph pre-training (KGP) framework, MuDoK, is proposed to enhance various AI tasks by leveraging large-scale knowledge graphs. This framework enables multi-domain collaborative pre-training and efficient prefix prompt tuning for diverse downstream tasks like recommendation and text understanding. The design is a plug-and-play prompt learning approach that can be adapted to different backbone models. To evaluate the effectiveness of MuDoK, a new open-source benchmark, KPI, was constructed with two large-scale KGs and six sub-domain tasks. Experimental results demonstrate significant performance gains, generality, efficiency, and transferability. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Knowledge graphs are like super-smart databases that help artificial intelligence (AI) do better jobs. Scientists want to make AI smarter by training computers on these databases before using them for other tasks. However, this process is complicated and not always open to the public. To solve this problem, researchers created a new way to train AI models called MuDoK. This approach makes it easier to use knowledge graphs for different AI tasks and allows multiple teams to work together more efficiently. The team also built a special testing ground, called KPI, to see how well their method works. They found that MuDoK makes AI models perform better and can be used with many different types of data. |
Keywords
» Artificial intelligence » Knowledge graph » Prompt » Transferability
